aaai 2021 论文列表
Thirty-Fifth AAAI Conference on Artificial Intelligence, AAAI 2021, Thirty-Third Conference on Innovative Applications of Artificial Intelligence, IAAI 2021, The Eleventh Symposium on Educational Advances in Artificial Intelligence, EAAI 2021, Virtual Event, February 2-9, 2021.
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Fashion Focus: Multi-modal Retrieval System for Video Commodity Localization in E-commerce.
MMKE: A Multi-Model Knowledge Extraction System from Unstructured Texts.
TAILOR: Teaching with Active and Incremental Learning for Object Registration.
IFDDS: An Anti-fraud Outbound Robot.
CogNet: Bridging Linguistic Knowledge, World Knowledge and Commonsense Knowledge.
EasyASR: A Distributed Machine Learning Platform for End-to-end Automatic Speech Recognition.
The Active Sensing Testbed.
ITRIX - an AI Enabled Solution for Orchestration of Recovery Instructions.
Software for Agent-based Network Simulation and Visualization.
Accelerating Data Discovery with an Ontology-driven Tool for an Enterprise-scale Data Lake Environment.
Integrating Pre-trained Model into Rule-based Dialogue Management.
SkeletonVis: Interactive Visualization for Understanding Adversarial Attacks on Human Action Recognition Models.
i-Parser: Interactive Parser Development Kit for Natural Language Processing.
RadarMath: An Intelligent Tutoring System for Math Education.
ACAT-G: An Interactive Learning Framework for Assisted Response Generation.
The Adapter-Bot: All-In-One Controllable Conversational Model.
DeepRobust: a Platform for Adversarial Attacks and Defenses.
A Novel Mountain Driving Unity Simulated Environment for Autonomous Vehicles.
CamouFinder: Finding Camouflaged Instances in Images.
Interactive Video Object Mask Annotation.
Proof of Learning (PoLe): Empowering Machine Learning with Consensus Building on Blockchains (Demo).
TODS: An Automated Time Series Outlier Detection System.
Democratizing Constraint Satisfaction Problems through Machine Learning.
Business Entity Matching with Siamese Graph Convolutional Networks.
RADAR-X: An Interactive Interface Pairing Contrastive Explanations with Revised Plan Suggestions.
Mobile-based Clock Drawing Test for Detecting Early Signs of Dementia.
AI-Empowered Decision Support for COVID-19 Social Distancing.
EasyRL: A Simple and Extensible Reinforcement Learning Framework.
Dialog Router: Automated Dialog Transition via Multi-Task Learning.
NEO: A System for Identifying New Emerging Occupation from Job Ads.
IBM Scenario Planning Advisor: A Neuro-Symbolic ERM Solution.
KAAPA: Knowledge Aware Answers from PDF Analysis.
Doc2Bot: Document grounded Bot Framework.
Bootstrapping Dialog Models from Human to Human Conversation Logs.
Juice: A Julia Package for Logic and Probabilistic Circuits.
Demonstration of the EMPATHIC Framework for Task Learning from Implicit Human Feedback.
ESO-MAPF: Bridging Discrete Planning and Continuous Execution in Multi-Agent Pathfinding.
OPRA: An Open-Source Online Preference Reporting and Aggregation System.
An Intelligent Assistant for Problem Behavior Management.
A Health-friendly Speaker Verification System Supporting Mask Wearing.
AutoText: An End-to-End AutoAI Framework for Text.
A Compression-Compilation Co-Design Framework Towards Real-Time Object Detection on Mobile Devices.
VEGA: a Virtual Environment for Exploring Gender Bias vs. Accuracy Trade-offs in AI Translation Services.
OzoMorph: Demonstrating Colored Multi-Agent Path Finding on Real Robots.
Exploring the Efficacy of Generic Drugs in Treating Cancer.
A Semantic Parsing and Reasoning-Based Approach to Knowledge Base Question Answering.
Bison Hacks the Yard: Assisting Underrepresented Students Overcome Impostor Syndrome with Augmented Reality and Artificial Intelligence.
MOTIF-Driven Contrastive Learning of Graph Representations.
Investigating Methods of Balancing Inequality and Efficiency in Ride Pooling.
Predictive Agent-Based Modeling of Natural Disasters Using Machine Learning.
Use of Computer Vision to Develop a Device to Assist Visually Impaired People with Social Distance.
Efficient Robust Music Genre Classification with Depthwise Separable Convolutions and Source Separation.
Exploration of Unknown Environments Using Deep Reinforcement Learning.
Affect-Aware Machine Learning Models for Deception Detection.
Probabilistic Robustness Quantification of Neural Networks.
The Price of Anarchy in ROSCAS with Risk Averse Agents.
Using Remote Sensing Imagery and Machine Learning to Predict Poaching in Wildlife Conservation Parks.
Analyzing Games with a Variable Number of Players.
Text Analysis for Understanding Symptoms of Social Anxiety in Student Veterans.
Evolving Spiking Circuit Motifs Using Weight Agnostic Neural Networks.
State-Wise Adaptive Discounting from Experience (SADE): A Novel Discounting Scheme for Reinforcement Learning (Student Abstract).
Knowledge-aware Dialogue Generation with Hybrid Attention (Student Abstract).
LAMS: A Location-aware Approach for Multimodal Summarization (Student Abstract).
Incorporating Bidirection-Interactive Information and Semantic Features for Relational Facts Extraction (Student Abstract).
Modeling High-order Interactions across Multi-interests for Micro-video Reommendation (Student Abstract).
Contextual Bandits with Delayed Feedback and Semi-supervised Learning (Student Abstract).
Zera-Shot Sentiment Analysis for Code-Mixed Data.
Improving the Morphology and Control Policy of Self-reconfiguring Modular Robots in Dynamic Environment (Student Abstract).
Enhancing Context-Based Meta-Reinforcement Learning Algorithms via An Efficient Task Encoder (Student Abstract).
Change or Not: A Simple Approach for Plug and Play Language Models on Sentiment Control.
MMIM: An Interpretable Regularization Method for Neural Networks (Student Abstract).
A Double Phases Generation Network for Yes or No Question Generation (Student Abstract).
Local Search for Diversified Top-k s-plex Search Problem (Student Abstract).
LB-DESPOT: Efficient Online POMDP Planning Considering Lower Bound in Action Selection (Student Abstract).
Towards Extracting Graph Neural Network Models via Prediction Queries (Student Abstract).
Remember More by Recalling Less: Investigating the Role of Batch Size in Continual Learning with Experience Replay (Student Abstract).
Measuring Vegetation Density in Marsh Grass Photographs Using Deep Neural Networks (Student Abstract).
Extending Policy Shaping to Continuous State Spaces (Student Abstract).
Multi-label Few-shot Learning with Semantic Inference (Student Abstract).
Is Each Layer Non-trivial in CNN? (Student Abstract).
Chinese Character Image Clustering and Classification Based on Object Embedding Model (Student Abstract).
A New Robust Subspace Recovery Algorithm (Student Abstract).
Mining Intelligent Patterns using SVAC for Precision Agriculture and Optimizing Irrigation (Student Abstract).
FACS: Fast Code-based Algorithm for Coalition Structure Generation (Student Abstract).
WildfireNet: Predicting Wildfire Profiles (Student Abstract).
Semi-Supervised Learning via Triplet Network Based Active Learning (Student Abstract).
Sampling Partial Acyclic Orientations in Chordal Graphs by the Lovasz Local Lemma (Student Abstract).
Scalable Partial Explainability in Neural Networks via Flexible Activation Functions (Student Abstract).
SecDD: Efficient and Secure Method for Remotely Training Neural Networks (Student Abstract).
Learning to Enhance Visual Quality via Hyperspectral Domain Mapping (Student Abstract).
Mental Actions and Explainability in Kripkean Semantics: What Else do I Know? (Student Abstract).
Neuro-Symbolic Techniques for Description Logic Reasoning (Student Abstract).
Quantum Binary Classification (Student Abstract).
Attention Beam: An Image Captioning Approach (Student Abstract).
Skills2Job: A Recommender System that Encodes Job Offer Embeddings on Graph Databases (Student Abstract).
Data Domain Change and Feature Selection to Predict Cardiac Pathology with a 2D Clinical Dataset and Convolutional Neural Networks (Student Abstract).
Are Chess Discussions Racist? An Adversarial Hate Speech Data Set (Student Abstract).
Generating Long Financial Report using Conditional Variational Autoencoders with Knowledge Distillation.
Automatic Optimal Multi-Agent Path Finding Algorithm Selector (Student Abstract).
SSA2D: Single Shot Actor-Action Detection in Videos (Student Abstract).
AuthNet: A Deep Learning Based Authentication Mechanism Using Temporal Facial Feature Movements (Student Abstract).
Context-Enhanced Entity and Relation Embedding for Knowledge Graph Completion (Student Abstract).
Successive Halving Top-k Operator.
Task Uncertainty Loss Reduce Negative Transfer in Asymmetric Multi-task Feature Learning (Student Abstract).
An Entity-Aware Adversarial Domain Adaptation Network for Cross-Domain Named Entity Recognition (Student Abstract).
Preventing Overfitting via Sample Reweighting for Recommender System Incremental Update (Student Abstract).
Solving JumpIN' Using Zero-Dependency Reinforcement Learning (Student Abstract).
A Method for Taxonomy-Aware Embeddings Evaluation (Student Abstract).
Deep Reinforcement Learning for a Dictionary Based Compression Schema (Student Abstract).
Improving Label Noise Robustness with Data Augmentation and Semi-Supervised Learning (Student Abstract).
Shallow-UWnet: Compressed Model for Underwater Image Enhancement (Student Abstract).
Two-Sided Fairness in Non-Personalised Recommendations (Student Abstract).
Toward Determining NFA Equivalence via QBFs (Student Abstract).
Source Separation and Depthwise Separable Convolutions for Computer Audition (Student Abstract).
Detection of Digital Manipulation in Facial Images (Student Abstract).
Improving the Performance-Compatibility Tradeoff with Personalized Objective Functions (Student Abstract).
RL Generalization in a Theory of Mind Game Through a Sleep Metaphor (Student Abstract).
A Context Aware Approach for Generating Natural Language Attacks.
Generating Adversarial yet Inconspicuous Patches with a Single Image (Student Abstract).
Semi-Discrete Social Recommendation (Student Abstract).
An Attention Based Multi-view Model for Sarcasm Cause Detection (Student Abstract).
A Quantum-inspired Complex-valued Representation for Encoding Sentiment Information (Student Abstract).
Information Block Detection in Infographic Based on Spatial Proximity and Structural Similarity (Student Abstract).
Towards Sample Efficient Agents through Algorithmic Alignment (Student Abstract).
Melodic Phrase Attention Network for Symbolic Data-based Music Genre Classification (Student Abstract).
A Nested Named Entity Recognition Model Based on Multi-agent Communication Mechanism (Student Abstract).
Domain Generalisation with Domain Augmented Supervised Contrastive Learning (Student Abstract).
Is Active Learning Always Beneficial? (Student Abstract).
Robustness to Missing Features using Hierarchical Clustering with Split Neural Networks (Student Abstract).
Leveraging on Deep Reinforcement Learning for Autonomous Safe Decision-Making in Highway On-ramp Merging (Student Abstract).
An Unfair Affinity Toward Fairness: Characterizing 70 Years of Social Biases in BHollywood (Student Abstract).
A Deep Learning Framework for Improving Lameness Identification in Dairy Cattle.
Compilation Complexity of Multi-Winner Voting Rules (Student Abstract).
Gradient-Based Localization and Spatial Attention for Confidence Measure in Fine-Grained Recognition using Deep Neural Networks.
Rotation-Invariant Gait Identification with Quaternion Convolutional Neural Networks (Student Abstract).
HetSAGE: Heterogenous Graph Neural Network for Relational Learning (Student Abstract).
Dethroning Aristocracy in Graphs via Adversarial Perturbations (Student Abstract).
Comparing Symbolic Models of Language via Bayesian Inference (Student Abstract).
EC-GAN: Low-Sample Classification using Semi-Supervised Algorithms and GANs (Student Abstract).
Pedestrian's Intention Recognition, Fusion of Handcrafted Features in a Deep Learning Approach.
Reinforcement Based Learning on Classification Task Yields Better Generalization and Adversarial Accuracy (Student Abstract).
Text Embedding Bank for Detailed Image Paragraph Captioning.
Global Fusion Attention for Vision and Language Understanding (Student Abstract).
RGB-D Scene Recognition based on Object-Scene Relation (Student Abstract).
Evaluating Meta-Reinforcement Learning through a HVAC Control Benchmark (Student Abstract).
Detecting Lexical Semantic Change across Corpora with Smooth Manifolds (Student Abstract).
Improving Aerial Instance Segmentation in the Dark with Self-Supervised Low Light Enhancement (Student Abstract).
Demonstrating the Equivalence of List Based and Aggregate Metrics to Measure the Diversity of Recommendations (Student Abstract).
Incorporating Curiosity into Personalized Ranking for Collaborative Filtering (Student Abstract).
Reducing Neural Network Parameter Initialization Into an SMT Problem (Student Abstract).
Passive learning of Timed Automata from logs (Student Abstract).
Multi-modal User Intent Classification Under the Scenario of Smart Factory (Student Abstract).
Robotic Manipulation with Reinforcement Learning, State Representation Learning, and Imitation Learning (Student Abstract).
NEAP-F: Network Epoch Accuracy Prediction Framework (Student Abstract).
BOSS: A Bi-directional Search Technique for Optimal Coalition Structure Generation with Minimal Overlapping (Student Abstract).
Fair Stable Matchings Under Correlated Preferences (Student Abstract).
Early Prediction of Children's Task Completion in a Tablet Tutor using Visual Features (Student Abstract).
Unsupervised Causal Knowledge Extraction from Text using Natural Language Inference (Student Abstract).
Encoding Temporal and Spatial Vessel Context using Self-Supervised Learning Model (Student Abstract).
Responsible Prediction Making of COVID-19 Mortality (Student Abstract).
Logic Guided Genetic Algorithms (Student Abstract).
Clustering Partial Lexicographic Preference Trees (Student Abstract).
Reward based Hebbian Learning in Direct Feedback Alignment (Student Abstract).
A Serverless Approach to Federated Learning Infrastructure Oriented for IoT/Edge Data Sources (Student Abstract).
Role of Optimizer on Network Fine-tuning for Adversarial Robustness (Student Abstract).
How Human Centered AI Will Contribute Towards Intelligent Gaming Systems.
Distributed Situation Awareness for Multi-agent Mission in Dynamic Environments: A Case Study of Multi-UAVs Wildfires Searching.
Multi-agent Reinforcement Learning for Decentralized Coalition Formation Games.
Towards Fair, Equitable, and Efficient Peer Review.
Safety Assurance for Systems with Machine Learning Components.
AI for Social Good: Between My Research and the Real World.
Robots that Help Humans Build Better Mental Models of Robots.
Transfer Learning of Engagement Recognition within Robot-Assisted Therapy for Children with Autism.
Constraint-Driven Learning of Logic Programs.
Relational Learning to Capture the Dynamics and Sparsity of Knowledge Graphs.
Screening for Depressed Individuals by Using Multimodal Social Media Data.
On Learning Deep Models with Imbalanced Data Distribution.
Artificial Intelligence and Machine Learning for Autonomous Agents that Learn to Plan and Operate in Unpredictable Dynamic Environments.
Perception Beyond Sensors Under Uncertainty.
Verification and Repair of Neural Networks.
Creating Interpretable Data-Driven Approaches for Remote Health Monitoring.
Effective Clustering of scRNA-seq Data to Identify Biomarkers without User Input.
A Computational Approach to Sign Language Understanding.
Model AI Assignments 2021.
Applied Machine Learning for Games: A Graduate School Course.
Web-based Platform for K-12 AI Education in China.
Teacher Perspectives on How To Train Your Robot: A Middle School AI and Ethics Curriculum.
Educational Question Mining At Scale: Prediction, Analysis and Personalization.
GANs Unplugged.
Teaching Tech to Talk: K-12 Conversational Artificial Intelligence Literacy Curriculum and Development Tools.
A Data-Driven Approach for Gin Rummy Hand Evaluation.
Designing a Hybrid AI Residency.
Introduction to Machine Learning with Robots and Playful Learning.
A Deterministic Neural Network Approach to Playing Gin Rummy.
A Highly-Parameterized Ensemble to Play Gin Rummy.
Opponent Hand Estimation in Gin Rummy Using Deep Neural Networks and Heuristic Strategies.
Knocking in the Game of Gin Rummy.
AI-Infused Collaborative Inquiry in Upper Elementary School: A Game-Based Learning Approach.
The Contour to Classification Game.
Modeling Expert Knowledge in a Heuristic-Based Gin Rummy Agent.
Why and What to Teach: AI Curriculum for Elementary School.
Student Knowledge Prediction for Teacher-Student Interaction.
PoseBlocks: A Toolkit for Creating (and Dancing) with AI.
Random Forests for Opponent Hand Estimation in Gin Rummy.
Deep Discourse Analysis for Generating Personalized Feedback in Intelligent Tutor Systems.
Learning Artificial Intelligence: Insights into How Youth Encounter and Build Understanding of AI Concepts.
Extracting Learned Discard and Knocking Strategies from a Gin Rummy Bot.
Evaluating Gin Rummy Hands Using Opponent Modeling and Myopic Meld Distance.
Estimating Card Fitness for Discard in Gin Rummy.
Opponent Hand Estimation in the Game of Gin Rummy.
Heisenbot: A Rule-Based Game Agent for Gin Rummy.
Visualizing NLP in Undergraduate Students' Learning about Natural Language.
What are GANs?: Introducing Generative Adversarial Networks to Middle School Students.
A Heuristic Evaluation Function for Hand Strength Estimation in Gin Rummy.
Preventing Repeated Real World AI Failures by Cataloging Incidents: The AI Incident Database.
Empirical Best Practices On Using Product-Specific Schema.org.
Combining Machine Learning and Human Experts to Predict Match Outcomes in Football: A Baseline Model.
Representing the Unification of Text Featurization using a Context-Free Grammar.
HetSeq: Distributed GPU Training on Heterogeneous Infrastructure.
Deep Epidemiological Modeling by Black-box Knowledge Distillation: An Accurate Deep Learning Model for COVID-19.
Device Fabrication Knowledge Extraction from Materials Science Literature.
Predicting Parking Availability from Mobile Payment Transactions with Positive Unlabeled Learning.
Carbon to Diamond: An Incident Remediation Assistant System From Site Reliability Engineers' Conversations in Hybrid Cloud Operations.
DeepCOVID: An Operational Deep Learning-driven Framework for Explainable Real-time COVID-19 Forecasting.
A Reciprocal Embedding Framework For Modelling Mutual Preferences.
Using Online Planning and Acting to Recover from Cyberattacks on Software-defined Networks.
Predicting Mining Industry Accidents with a Multitask Learning Approach.
SKATE: A Natural Language Interface for Encoding Structured Knowledge.
Reinforcement Learning-based Product Delivery Frequency Control.
Twitter Event Summarization by Exploiting Semantic Terms and Graph Network.
Personalizing Individual Comfort in the Group Setting.
VRU Pose-SSD: Multiperson Pose Estimation For Automated Driving.
Spatiotemporal Graph Neural Network for Performance Prediction of Photovoltaic Power Systems.
Over-MAP: Structural Attention Mechanism and Automated Semantic Segmentation Ensembled for Uncertainty Prediction.
Where there's Smoke, there's Fire: Wildfire Risk Predictive Modeling via Historical Climate Data.
JEL: Applying End-to-End Neural Entity Linking in JPMorgan Chase.
Shape-based Feature Engineering for Solar Flare Prediction.
Identification of Abnormal States in Videos of Ants Undergoing Social Phase Change.
Deepening the Sense of Touch in Planetary Exploration with Geometric and Topological Deep Learning.
Data-Driven Multimodal Patrol Planning for Anti-poaching.
Topological Machine Learning Methods for Power System Responses to Contingencies.
Attr2Style: A Transfer Learning Approach for Inferring Fashion Styles via Apparel Attributes.
Ontology-Enriched Query Answering on Relational Databases.
Path to Automating Ocean Health Monitoring.
Finding Needles in Heterogeneous Haystacks.
A Novel AI-based Methodology for Identifying Cyber Attacks in Honey Pots.
Enhancing E-commerce Recommender System Adaptability with Online Deep Controllable Learning-To-Rank.
Mars Image Content Classification: Three Years of NASA Deployment and Recent Advances.
An Automated Engineering Assistant: Learning Parsers for Technical Drawings.
Tool for Automated Tax Coding of Invoices.
Using Unsupervised Learning for Data-driven Procurement Demand Aggregation.
Deeplite NeutrinoTM: A BlackBox Framework for Constrained Deep Learning Model Optimization.
EeLISA: Combating Global Warming Through the Rapid Analysis of Eelgrass Wasting Disease.
Author Homepage Discovery in CiteSeerX.
Robust PDF Document Conversion using Recurrent Neural Networks.
Accurate and Interpretable Machine Learning for Transparent Pricing of Health Insurance Plans.
Comparison Lift: Bandit-based Experimentation System for Online Advertising.
Automated Reasoning and Learning for Automated Payroll Management.
An End-to-End Solution for Named Entity Recognition in eCommerce Search.
Preclinical Stage Alzheimer's Disease Detection Using Magnetic Resonance Image Scans.
Empowering Conversational AI is a Trip to Mars: Progress and Future of Open Domain Human-Computer Dialogues.
Thou Shalt Love Thy Neighbor as Thyself When Thou Playest: Altruism in Game Theory.
Unifying Principles and Metrics for Safe and Assistive AI.
Lifelong and Continual Learning Dialogue Systems: Learning during Conversation.
Improving Causal Inference by Increasing Model Expressiveness.
Towards a Unifying Framework for Formal Theories of Novelty.
Thinking Fast and Slow in AI.
Land Deformation Prediction via Slope-Aware Graph Neural Networks.
Forecasting Reservoir Inflow via Recurrent Neural ODEs.
HOT-VAE: Learning High-Order Label Correlation for Multi-Label Classification via Attention-Based Variational Autoencoders.
Traffic Flow Forecasting with Spatial-Temporal Graph Diffusion Network.
Joint Incentive Optimization of Customer and Merchant in Mobile Payment Marketing.
Early Safety Warnings for Long-Distance Pipelines: A Distributed Optical Fiber Sensor Machine Learning Approach.
Predicting Forest Fire Using Remote Sensing Data And Machine Learning.
Dual-Mandate Patrols: Multi-Armed Bandits for Green Security.
Multi-Layer Networks for Ensemble Precipitation Forecasts Postprocessing.
Modeling the Field Value Variations and Field Interactions Simultaneously for Fraud Detection.
Clinical Trial of an AI-Augmented Intervention for HIV Prevention in Youth Experiencing Homelessness.
Evidence Aware Neural Pornographic Text Identification for Child Protection.
Minimizing Energy Use of Mixed-Fleet Public Transit for Fixed-Route Service.
Degree Planning with PLAN-BERT: Multi-Semester Recommendation Using Future Courses of Interest.
Combining Machine Learning & Reasoning for Biodiversity Data Intelligence.
RainBench: Towards Data-Driven Global Precipitation Forecasting from Satellite Imagery.
We Don't Speak the Same Language: Interpreting Polarization through Machine Translation.
A Universal 2-state n-action Adaptive Management Solver.
Goten: GPU-Outsourcing Trusted Execution of Neural Network Training.
HateXplain: A Benchmark Dataset for Explainable Hate Speech Detection.
Mitigating Political Bias in Language Models through Reinforced Calibration.
Subverting Privacy-Preserving GANs: Hiding Secrets in Sanitized Images.
Court Opinion Generation from Case Fact Description with Legal Basis.
Prediction of Landfall Intensity, Location, and Time of a Tropical Cyclone.
Computational Visual Ceramicology: Matching Image Outlines to Catalog Sketches.
Project RISE: Recognizing Industrial Smoke Emissions.
Abusive Language Detection in Heterogeneous Contexts: Dataset Collection and the Role of Supervised Attention.
Fair and Interpretable Algorithmic Hiring using Evolutionary Many Objective Optimization.
Predicting Flashover Occurrence using Surrogate Temperature Data.
K-N-MOMDPs: Towards Interpretable Solutions for Adaptive Management.
Retrieve and Revise: Improving Peptide Identification with Similar Mass Spectra.
Using Radio Archives for Low-Resource Speech Recognition: Towards an Intelligent Virtual Assistant for Illiterate Users.
Harnessing Social Media to Identify Homeless Youth At-Risk of Substance Use.
Graph Learning for Inverse Landscape Genetics.
Detection and Prediction of Nutrient Deficiency Stress using Longitudinal Aerial Imagery.
Real-time Tropical Cyclone Intensity Estimation by Handling Temporally Heterogeneous Satellite Data.
Accelerating Ecological Sciences from Above: Spatial Contrastive Learning for Remote Sensing.
Learning Augmented Methods for Matching: Improving Invasive Species Management and Urban Mobility.
Intelligent Recommendations for Citizen Science.
Fairness in Influence Maximization through Randomization.
Unsupervised Summarization for Chat Logs with Topic-Oriented Ranking and Context-Aware Auto-Encoders.
Topic-Oriented Spoken Dialogue Summarization for Customer Service with Saliency-Aware Topic Modeling.
Neural Sentence Ordering Based on Constraint Graphs.
Clinical Temporal Relation Extraction with Probabilistic Soft Logic Regularization and Global Inference.
What the Role is vs. What Plays the Role: Semi-Supervised Event Argument Extraction via Dual Question Answering.
An Adaptive Hybrid Framework for Cross-domain Aspect-based Sentiment Analysis.
IsoBN: Fine-Tuning BERT with Isotropic Batch Normalization.
Document-Level Relation Extraction with Adaptive Thresholding and Localized Context Pooling.
EvaLDA: Efficient Evasion Attacks Towards Latent Dirichlet Allocation.
A Neural Group-wise Sentiment Analysis Model with Data Sparsity Awareness.
MTAAL: Multi-Task Adversarial Active Learning for Medical Named Entity Recognition and Normalization.
CARE: Commonsense-Aware Emotional Response Generation with Latent Concepts.
Keyword-Guided Neural Conversational Model.
Stylized Dialogue Response Generation Using Stylized Unpaired Texts.
Interactive Speech and Noise Modeling for Speech Enhancement.
Automatic Curriculum Learning With Over-repetition Penalty for Dialogue Policy Learning.
LIREx: Augmenting Language Inference with Relevant Explanations.
A Unified Multi-Task Learning Framework for Joint Extraction of Entities and Relations.
Dynamic Modeling Cross- and Self-Lattice Attention Network for Chinese NER.
Retrospective Reader for Machine Reading Comprehension.
News Content Completion with Location-Aware Image Selection.
Unsupervised Abstractive Dialogue Summarization for Tete-a-Tetes.
Denoising Distantly Supervised Named Entity Recognition via a Hypergeometric Probabilistic Model.
Circles are like Ellipses, or Ellipses are like Circles? Measuring the Degree of Asymmetry of Static and Contextual Word Embeddings and the Implications to Representation Learning.
Graph-Based Tri-Attention Network for Answer Ranking in CQA.
Self-supervised Bilingual Syntactic Alignment for Neural Machine Translation.
Learning to Check Contract Inconsistencies.
Semantics-Aware Inferential Network for Natural Language Understanding.
Future-Guided Incremental Transformer for Simultaneous Translation.
MERL: Multimodal Event Representation Learning in Heterogeneous Embedding Spaces.
Making the Relation Matters: Relation of Relation Learning Network for Sentence Semantic Matching.
TaLNet: Voice Reconstruction from Tongue and Lip Articulation with Transfer Learning from Text-to-Speech Synthesis.
Continuous Self-Attention Models with Neural ODE Networks.
Writing Polishment with Simile: Task, Dataset and A Neural Approach.
Deep Open Intent Classification with Adaptive Decision Boundary.
Discovering New Intents with Deep Aligned Clustering.
Accelerating Neural Machine Translation with Partial Word Embedding Compression.
Multi-modal Graph Fusion for Named Entity Recognition with Targeted Visual Guidance.
Multi-modal Multi-label Emotion Recognition with Heterogeneous Hierarchical Message Passing.
Building Interpretable Interaction Trees for Deep NLP Models.
UWSpeech: Speech to Speech Translation for Unwritten Languages.
Meta-Curriculum Learning for Domain Adaptation in Neural Machine Translation.
Probing Product Description Generation via Posterior Distillation.
What's the Best Place for an AI Conference, Vancouver or _______: Why Completing Comparative Questions is Difficult.
Reinforced Multi-Teacher Selection for Knowledge Distillation.
Simpson's Bias in NLP Training.
Unanswerable Question Correction in Question Answering over Personal Knowledge Base.
Contrastive Triple Extraction with Generative Transformer.
Adversarial Language Games for Advanced Natural Language Intelligence.
Open Domain Dialogue Generation with Latent Images.
UBAR: Towards Fully End-to-End Task-Oriented Dialog System with GPT-2.
Multi-Document Transformer for Personality Detection.
Style-transfer and Paraphrase: Looking for a Sensible Semantic Similarity Metric.
Human-Level Interpretable Learning for Aspect-Based Sentiment Analysis.
GDPNet: Refining Latent Multi-View Graph for Relation Extraction.
A Supervised Multi-Head Self-Attention Network for Nested Named Entity Recognition.
Topic-Aware Multi-turn Dialogue Modeling.
Document-Level Relation Extraction with Reconstruction.
Learning an Effective Context-Response Matching Model with Self-Supervised Tasks for Retrieval-based Dialogues.
Entity Structure Within and Throughout: Modeling Mention Dependencies for Document-Level Relation Extraction.
Nyströmformer: A Nyström-based Algorithm for Approximating Self-Attention.
Enabling Fast and Universal Audio Adversarial Attack Using Generative Model.
Improving Tree-Structured Decoder Training for Code Generation via Mutual Learning.
Adversarial Meta Sampling for Multilingual Low-Resource Speech Recognition.
Does Head Label Help for Long-Tailed Multi-Label Text Classification.
Context-Guided BERT for Targeted Aspect-Based Sentiment Analysis.
A Controllable Model of Grounded Response Generation.
MELINDA: A Multimodal Dataset for Biomedical Experiment Method Classification.
TextGAIL: Generative Adversarial Imitation Learning for Text Generation.
Evidence Inference Networks for Interpretable Claim Verification.
On Scalar Embedding of Relative Positions in Attention Models.
Do Response Selection Models Really Know What's Next? Utterance Manipulation Strategies for Multi-turn Response Selection.
MLE-Guided Parameter Search for Task Loss Minimization in Neural Sequence Modeling.
Robustness to Spurious Correlations in Text Classification via Automatically Generated Counterfactuals.
Code Completion by Modeling Flattened Abstract Syntax Trees as Graphs.
NaturalConv: A Chinese Dialogue Dataset Towards Multi-turn Topic-driven Conversation.
Adversarial Training with Fast Gradient Projection Method against Synonym Substitution Based Text Attacks.
Generating Diversified Comments via Reader-Aware Topic Modeling and Saliency Detection.
Tracking Interaction States for Multi-Turn Text-to-SQL Semantic Parsing.
Bridging the Domain Gap: Improve Informal Language Translation via Counterfactual Domain Adaptation.
Tune-In: Training Under Negative Environments with Interference for Attention Networks Simulating Cocktail Party Effect.
Effective Slot Filling via Weakly-Supervised Dual-Model Learning.
Encoding Syntactic Knowledge in Transformer Encoder for Intent Detection and Slot Filling.
Exploring Explainable Selection to Control Abstractive Summarization.
KEML: A Knowledge-Enriched Meta-Learning Framework for Lexical Relation Classification.
FL-MSRE: A Few-Shot Learning based Approach to Multimodal Social Relation Extraction.
Learning from My Friends: Few-Shot Personalized Conversation Systems via Social Networks.
Ideography Leads Us to the Field of Cognition: A Radical-Guided Associative Model for Chinese Text Classification.
A Bidirectional Multi-paragraph Reading Model for Zero-shot Entity Linking.
VisualMRC: Machine Reading Comprehension on Document Images.
Unsupervised Learning of Deterministic Dialogue Structure with Edge-Enhanced Graph Auto-Encoder.
RpBERT: A Text-image Relation Propagation-based BERT Model for Multimodal NER.
Progressive Multi-task Learning with Controlled Information Flow for Joint Entity and Relation Extraction.
Re-TACRED: Addressing Shortcomings of the TACRED Dataset.
Improving Commonsense Causal Reasoning by Adversarial Training and Data Augmentation.
Fact-Enhanced Synthetic News Generation.
A Simple and Effective Self-Supervised Contrastive Learning Framework for Aspect Detection.
Learning Contextual Representations for Semantic Parsing with Generation-Augmented Pre-Training.
SongMASS: Automatic Song Writing with Pre-training and Alignment Constraint.
DialogXL: All-in-One XLNet for Multi-Party Conversation Emotion Recognition.
Nutri-bullets: Summarizing Health Studies by Composing Segments.
Learning from the Best: Rationalizing Predictions by Adversarial Information Calibration.
Semantics Altering Modifications for Evaluating Comprehension in Machine Reading.
Exploring Transfer Learning For End-to-End Spoken Language Understanding.
Automated Cross-prompt Scoring of Essay Traits.
Towards Semantics-Enhanced Pre-Training: Can Lexicon Definitions Help Learning Sentence Meanings?
Guiding Non-Autoregressive Neural Machine Translation Decoding with Reordering Information.
Reinforced History Backtracking for Conversational Question Answering.
Co-GAT: A Co-Interactive Graph Attention Network for Joint Dialog Act Recognition and Sentiment Classification.
Exploring Auxiliary Reasoning Tasks for Task-oriented Dialog Systems with Meta Cooperative Learning.
A Student-Teacher Architecture for Dialog Domain Adaptation Under the Meta-Learning Setting.
Conceptualized and Contextualized Gaussian Embedding.
Revisiting Mahalanobis Distance for Transformer-Based Out-of-Domain Detection.
Data Augmentation for Abstractive Query-Focused Multi-Document Summarization.
ALP-KD: Attention-Based Layer Projection for Knowledge Distillation.
XL-WSD: An Extra-Large and Cross-Lingual Evaluation Framework for Word Sense Disambiguation.
On the Softmax Bottleneck of Recurrent Language Models.
Movie Summarization via Sparse Graph Construction.
Copy That! Editing Sequences by Copying Spans.
The Heads Hypothesis: A Unifying Statistical Approach Towards Understanding Multi-Headed Attention in BERT.
Dialog Policy Learning for Joint Clarification and Active Learning Queries.
Knowledge-aware Named Entity Recognition with Alleviating Heterogeneity.
Disentangled Motif-aware Graph Learning for Phrase Grounding.
MASKER: Masked Keyword Regularization for Reliable Text Classification.
Continual Learning for Named Entity Recognition.
How Robust are Model Rankings : A Leaderboard Customization Approach for Equitable Evaluation.
Variational Inference for Learning Representations of Natural Language Edits.
A Joint Training Dual-MRC Framework for Aspect Based Sentiment Analysis.
Bridging Towers of Multi-task Learning with a Gating Mechanism for Aspect-based Sentiment Analysis and Sequential Metaphor Identification.
Generating Natural Language Attacks in a Hard Label Black Box Setting.
Generate Your Counterfactuals: Towards Controlled Counterfactual Generation for Text.
Knowledge-driven Data Construction for Zero-shot Evaluation in Commonsense Question Answering.
LET: Linguistic Knowledge Enhanced Graph Transformer for Chinese Short Text Matching.
Span-Based Event Coreference Resolution.
UNICORN on RAINBOW: A Universal Commonsense Reasoning Model on a New Multitask Benchmark.
SCRUPLES: A Corpus of Community Ethical Judgments on 32, 000 Real-Life Anecdotes.
On the Importance of Word Order Information in Cross-lingual Sequence Labeling.
CrossNER: Evaluating Cross-Domain Named Entity Recognition.
Generating CCG Categories.
A Graph Reasoning Network for Multi-turn Response Selection via Customized Pre-training.
Faster Depth-Adaptive Transformers.
Towards Faithfulness in Open Domain Table-to-text Generation from an Entity-centric View.
Filling the Gap of Utterance-aware and Speaker-aware Representation for Multi-turn Dialogue.
How to Train Your Agent to Read and Write.
Natural Language Inference in Context - Investigating Contextual Reasoning over Long Texts.
Converse, Focus and Guess - Towards Multi-Document Driven Dialogue.
Neural Sentence Simplification with Semantic Dependency Information.
Graph-Evolving Meta-Learning for Low-Resource Medical Dialogue Generation.
Hierarchical Coherence Modeling for Document Quality Assessment.
Infusing Multi-Source Knowledge with Heterogeneous Graph Neural Network for Emotional Conversation Generation.
Finding Sparse Structures for Domain Specific Neural Machine Translation.
An Unsupervised Sampling Approach for Image-Sentence Matching Using Document-level Structural Information.
An Efficient Transformer Decoder with Compressed Sub-layers.
Interpretable NLG for Task-oriented Dialogue Systems with Heterogeneous Rendering Machines.
TSQA: Tabular Scenario Based Question Answering.
Merging Statistical Feature via Adaptive Gate for Improved Text Classification.
HopRetriever: Retrieve Hops over Wikipedia to Answer Complex Questions.
Quantum-inspired Neural Network for Conversational Emotion Recognition.
ACT: an Attentive Convolutional Transformer for Efficient Text Classification.
The Style-Content Duality of Attractiveness: Learning to Write Eye-Catching Headlines via Disentanglement.
Towards Topic-Aware Slide Generation For Academic Papers With Unsupervised Mutual Learning.
Multi-view Inference for Relation Extraction with Uncertain Knowledge.
Improving the Efficiency and Effectiveness for BERT-based Entity Resolution.
Learning Light-Weight Translation Models from Deep Transformer.
Have We Solved The Hard Problem? It's Not Easy! Contextual Lexical Contrast as a Means to Probe Neural Coherence.
Multi-SpectroGAN: High-Diversity and High-Fidelity Spectrogram Generation with Adversarial Style Combination for Speech Synthesis.
SALNet: Semi-supervised Few-Shot Text Classification with Attention-based Lexicon Construction.
The Gap on Gap: Tackling the Problem of Differing Data Distributions in Bias-Measuring Datasets.
Self-supervised Pre-training and Contrastive Representation Learning for Multiple-choice Video QA.
FIXMYPOSE: Pose Correctional Captioning and Retrieval.
Hierarchical Macro Discourse Parsing Based on Topic Segmentation.
EQG-RACE: Examination-Type Question Generation.
Flexible Non-Autoregressive Extractive Summarization with Threshold: How to Extract a Non-Fixed Number of Summary Sentences.
DDRel: A New Dataset for Interpersonal Relation Classification in Dyadic Dialogues.
Dynamic Hybrid Relation Exploration Network for Cross-Domain Context-Dependent Semantic Parsing.
Unsupervised Learning of Discourse Structures using a Tree Autoencoder.
Audio-Oriented Multimodal Machine Comprehension via Dynamic Inter- and Intra-modality Attention.
Distribution Matching for Rationalization.
Adaptive Beam Search Decoding for Discrete Keyphrase Generation.
Story Ending Generation with Multi-Level Graph Convolutional Networks over Dependency Trees.
Entity Guided Question Generation with Contextual Structure and Sequence Information Capturing.
SARG: A Novel Semi Autoregressive Generator for Multi-turn Incomplete Utterance Restoration.
HARGAN: Heterogeneous Argument Attention Network for Persuasiveness Prediction.
Few-shot Learning for Multi-label Intent Detection.
C2C-GenDA: Cluster-to-Cluster Generation for Data Augmentation of Slot Filling.
It Takes Two to Empathize: One to Seek and One to Provide.
SMART: A Situation Model for Algebra Story Problems via Attributed Grammar.
Towards Fully Automated Manga Translation.
Show Me How To Revise: Improving Lexically Constrained Sentence Generation with XLNet.
Synchronous Interactive Decoding for Multilingual Neural Machine Translation.
Humor Knowledge Enriched Transformer for Understanding Multimodal Humor.
Self-Attention Attribution: Interpreting Information Interactions Inside Transformer.
Sketch and Customize: A Counterfactual Story Generator.
BERT & Family Eat Word Salad: Experiments with Text Understanding.
Iterative Utterance Segmentation for Neural Semantic Parsing.
Label Confusion Learning to Enhance Text Classification Models.
Read, Retrospect, Select: An MRC Framework to Short Text Entity Linking.
DialogBERT: Discourse-Aware Response Generation via Learning to Recover and Rank Utterances.
Perception Score: A Learned Metric for Open-ended Text Generation Evaluation.
Fake it Till You Make it: Self-Supervised Semantic Shifts for Monolingual Word Embedding Tasks.
Analogy Training Multilingual Encoders.
Question-Driven Span Labeling Model for Aspect-Opinion Pair Extraction.
Judgment Prediction via Injecting Legal Knowledge into Neural Networks.
Paragraph-level Commonsense Transformers with Recurrent Memory.
A Theoretical Analysis of the Repetition Problem in Text Generation.
Nested Named Entity Recognition with Partially-Observed TreeCRFs.
LRC-BERT: Latent-representation Contrastive Knowledge Distillation for Natural Language Understanding.
More the Merrier: Towards Multi-Emotion and Intensity Controllable Response Generation.
Multi-View Feature Representation for Dialogue Generation with Bidirectional Distillation.
End-to-end Semantic Role Labeling with Neural Transition-based Model.
Encoder-Decoder Based Unified Semantic Role Labeling with Label-Aware Syntax.
Rethinking Boundaries: End-To-End Recognition of Discontinuous Mentions with Pointer Networks.
FILTER: An Enhanced Fusion Method for Cross-lingual Language Understanding.
Knowledge-aware Leap-LSTM: Integrating Prior Knowledge into Leap-LSTM towards Faster Long Text Classification.
MultiTalk: A Highly-Branching Dialog Testbed for Diverse Conversations.
Listen, Understand and Translate: Triple Supervision Decouples End-to-end Speech-to-text Translation.
Consecutive Decoding for Speech-to-text Translation.
We Can Explain Your Research in Layman's Terms: Towards Automating Science Journalism at Scale.
DirectQE: Direct Pretraining for Machine Translation Quality Estimation.
How Linguistically Fair Are Multilingual Pre-Trained Language Models?
Adaptive Prior-Dependent Correction Enhanced Reinforcement Learning for Natural Language Generation.
Meta-Transfer Learning for Low-Resource Abstractive Summarization.
Reasoning in Dialog: Improving Response Generation by Context Reading Comprehension.
Empower Distantly Supervised Relation Extraction with Collaborative Adversarial Training.
Bidirectional Machine Reading Comprehension for Aspect Sentiment Triplet Extraction.
A Lightweight Neural Model for Biomedical Entity Linking.
Weakly-Supervised Hierarchical Models for Predicting Persuasive Strategies in Good-faith Textual Requests.
Aspect-Level Sentiment-Controllable Review Generation with Mutual Learning Framework.
Lexically Constrained Neural Machine Translation with Explicit Alignment Guidance.
Simple or Complex? Learning to Predict Readability of Bengali Texts.
Extracting Zero-shot Structured Information from Form-like Documents: Pretraining with Keys and Triggers.
Brain Decoding Using fNIRS.
Learning to Rationalize for Nonmonotonic Reasoning with Distant Supervision.
Multilingual Transfer Learning for QA using Translation as Data Augmentation.
Benchmarking Knowledge-Enhanced Commonsense Question Answering via Knowledge-to-Text Transformation.
One SPRING to Rule Them Both: Symmetric AMR Semantic Parsing and Generation without a Complex Pipeline.
Knowledge-driven Natural Language Understanding of English Text and its Applications.
Contextualized Rewriting for Text Summarization.
Learning to Copy Coherent Knowledge for Response Generation.
Segatron: Segment-Aware Transformer for Language Modeling and Understanding.
Joint Semantic Analysis with Document-Level Cross-Task Coherence Rewards.
Multi-Dimensional Explanation of Target Variables from Documents.
Enhancing Scientific Papers Summarization with Citation Graph.
Unsupervised Opinion Summarization with Content Planning.
Segmentation of Tweets with URLs and its Applications to Sentiment Analysis.
Empirical Regularization for Synthetic Sentence Pairs in Unsupervised Neural Machine Translation.
GATE: Graph Attention Transformer Encoder for Cross-lingual Relation and Event Extraction.
Improving Maximum k-plex Solver via Second-Order Reduction and Graph Color Bounding.
Combining Reinforcement Learning with Lin-Kernighan-Helsgaun Algorithm for the Traveling Salesman Problem.
Accelerated Combinatorial Search for Outlier Detection with Provable Bound on Sub-Optimality.
Learning Branching Heuristics for Propositional Model Counting.
Bayes DistNet - A Robust Neural Network for Algorithm Runtime Distribution Predictions.
Multi-Goal Multi-Agent Path Finding via Decoupled and Integrated Goal Vertex Ordering.
Weighting-based Variable Neighborhood Search for Optimal Camera Placement.
Deep Innovation Protection: Confronting the Credit Assignment Problem in Training Heterogeneous Neural Architectures.
Policy-Guided Heuristic Search with Guarantees.
Single Player Monte-Carlo Tree Search Based on the Plackett-Luce Model.
Correlation-Aware Heuristic Search for Intelligent Virtual Machine Provisioning in Cloud Systems.
EECBS: A Bounded-Suboptimal Search for Multi-Agent Path Finding.
Submodular Span, with Applications to Conditional Data Summarization.
Enhancing Balanced Graph Edge Partition with Effective Local Search.
Efficient Bayesian Network Structure Learning via Parameterized Local Search on Topological Orderings.
OpEvo: An Evolutionary Method for Tensor Operator Optimization.
Choosing the Initial State for Online Replanning.
Multi-Objective Submodular Maximization by Regret Ratio Minimization with Theoretical Guarantee.
Theoretical Analyses of Multi-Objective Evolutionary Algorithms on Multi-Modal Objectives.
Pareto Optimization for Subset Selection with Dynamic Partition Matroid Constraints.
Escaping Local Optima with Non-Elitist Evolutionary Algorithms.
Symmetry Breaking for k-Robust Multi-Agent Path Finding.
NuQClq: An Effective Local Search Algorithm for Maximum Quasi-Clique Problem.
Parameterized Algorithms for MILPs with Small Treedepth.
f-Aware Conflict Prioritization & Improved Heuristics For Conflict-Based Search.
Combining Preference Elicitation with Local Search and Greedy Search for Matroid Optimization.
Generalization in Portfolio-Based Algorithm Selection.
A Fast Exact Algorithm for the Resource Constrained Shortest Path Problem.
Bounding Causal Effects on Continuous Outcome.
Polynomial-Time Algorithms for Counting and Sampling Markov Equivalent DAGs.
Learning the Parameters of Bayesian Networks from Uncertain Data.
Robust Contextual Bandits via Bootstrapping.
Probabilistic Dependency Graphs.
Estimation of Spectral Risk Measures.
A New Bounding Scheme for Influence Diagrams.
Submodel Decomposition Bounds for Influence Diagrams.
Learning Continuous High-Dimensional Models using Mutual Information and Copula Bayesian Networks.
Instrumental Variable-based Identification for Causal Effects using Covariate Information.
Relational Boosted Bandits.
Estimating Identifiable Causal Effects through Double Machine Learning.
A Generative Adversarial Framework for Bounding Confounded Causal Effects.
High Dimensional Level Set Estimation with Bayesian Neural Network.
Scalable First-Order Methods for Robust MDPs.
Uncertainty Quantification in CNN Through the Bootstrap of Convex Neural Networks.
Better Bounds on the Adaptivity Gap of Influence Maximization under Full-adoption Feedback.
GO Hessian for Expectation-Based Objectives.
Group Fairness by Probabilistic Modeling with Latent Fair Decisions.
Multi-Decoder Attention Model with Embedding Glimpse for Solving Vehicle Routing Problems.
Competitive Analysis for Two-Level Ski-Rental Problem.
Asking the Right Questions: Learning Interpretable Action Models Through Query Answering.
Dynamic Automaton-Guided Reward Shaping for Monte Carlo Tree Search.
On the Optimal Efficiency of A* with Dominance Pruning.
Faster Stackelberg Planning via Symbolic Search and Information Sharing.
A Complexity-theoretic Analysis of Green Pickup-and-Delivery Problems.
Online Action Recognition.
Symbolic Search for Oversubscription Planning.
Planning with Learned Object Importance in Large Problem Instances using Graph Neural Networks.
Improved Knowledge Modeling and Its Use for Signaling in Multi-Agent Planning with Partial Observability.
Saturated Post-hoc Optimization for Classical Planning.
An LP-Based Approach for Goal Recognition as Planning.
Minimax Regret Optimisation for Robust Planning in Uncertain Markov Decision Processes.
Latent Independent Excitation for Generalizable Sensor-based Cross-Person Activity Recognition.
Faster and Better Simple Temporal Problems.
Revealing Hidden Preconditions and Effects of Compound HTN Planning Tasks - A Complexity Analysis.
Synthesis of Search Heuristics for Temporal Planning via Reinforcement Learning.
Improved POMDP Tree Search Planning with Prioritized Action Branching.
Bayesian Optimized Monte Carlo Planning.
Progression Heuristics for Planning with Probabilistic LTL Constraints.
On-line Learning of Planning Domains from Sensor Data in PAL: Scaling up to Large State Spaces.
Branch and Price for Bus Driver Scheduling with Complex Break Constraints.
Bike-Repositioning Using Volunteers: Crowd Sourcing with Choice Restriction.
Endomorphisms of Classical Planning Tasks.
Landmark Generation in HTN Planning.
Equitable Scheduling on a Single Machine.
Revisiting Dominance Pruning in Decoupled Search.
Learning General Planning Policies from Small Examples Without Supervision.
Robust Finite-State Controllers for Uncertain POMDPs.
GLIB: Efficient Exploration for Relational Model-Based Reinforcement Learning via Goal-Literal Babbling.
Successor Feature Sets: Generalizing Successor Representations Across Policies.
General Policies, Representations, and Planning Width.
A Multivariate Complexity Analysis of the Material Consumption Scheduling Problem.
Symbolic Search for Optimal Total-Order HTN Planning.
Responsibility Attribution in Parameterized Markovian Models.
Contract Scheduling With Predictions.
Constrained Risk-Averse Markov Decision Processes.
Computing Plan-Length Bounds Using Lengths of Longest Paths.
Decision-Guided Weighted Automata Extraction from Recurrent Neural Networks.
i-Algebra: Towards Interactive Interpretability of Deep Neural Networks.
Invertible Concept-based Explanations for CNN Models with Non-negative Concept Activation Vectors.
Tightening Robustness Verification of Convolutional Neural Networks with Fine-Grained Linear Approximation.
Improving Robustness to Model Inversion Attacks via Mutual Information Regularization.
Ethically Compliant Sequential Decision Making.
Exploring the Vulnerability of Deep Neural Networks: A Study of Parameter Corruption.
Explaining Convolutional Neural Networks through Attribution-Based Input Sampling and Block-Wise Feature Aggregation.
Fair Influence Maximization: a Welfare Optimization Approach.
Comprehension and Knowledge.
Ethical Dilemmas in Strategic Games.
Interpreting Deep Neural Networks with Relative Sectional Propagation by Analyzing Comparative Gradients and Hostile Activations.
Outlier Impact Characterization for Time Series Data.
How RL Agents Behave When Their Actions Are Modified.
On Generating Plausible Counterfactual and Semi-Factual Explanations for Deep Learning.
Ordered Counterfactual Explanation by Mixed-Integer Linear Optimization.
Differentially Private Clustering via Maximum Coverage.
Visualization of Supervised and Self-Supervised Neural Networks via Attribution Guided Factorization.
PenDer: Incorporating Shape Constraints via Penalized Derivatives.
On the Verification of Neural ODEs with Stochastic Guarantees.
Amnesiac Machine Learning.
Fair Representations by Compression.
Individual Fairness in Kidney Exchange Programs.
Agent Incentives: A Causal Perspective.
Epistemic Logic of Know-Who.
Verifiable Machine Ethics in Changing Contexts.
A Unified Taylor Framework for Revisiting Attribution Methods.
Robustness of Accuracy Metric and its Inspirations in Learning with Noisy Labels.
Beyond Class-Conditional Assumption: A Primary Attempt to Combat Instance-Dependent Label Noise.
FIMAP: Feature Importance by Minimal Adversarial Perturbation.
Bayes-TrEx: a Bayesian Sampling Approach to Model Transparency by Example.
TripleTree: A Versatile Interpretable Representation of Black Box Agents and their Environments.
Is the Most Accurate AI the Best Teammate? Optimizing AI for Teamwork.
Explaining A Black-box By Using A Deep Variational Information Bottleneck Approach.
Coordination Between Individual Agents in Multi-Agent Reinforcement Learning.
Efficient Querying for Cooperative Probabilistic Commitments.
Maintenance of Social Commitments in Multiagent Systems.
Contract-based Inter-user Usage Coordination in Free-floating Car Sharing.
Value-Decomposition Multi-Agent Actor-Critics.
Evolutionary Game Theory Squared: Evolving Agents in Endogenously Evolving Zero-Sum Games.
Synchronous Dynamical Systems on Directed Acyclic Graphs: Complexity and Algorithms.
Newton Optimization on Helmholtz Decomposition for Continuous Games.
Anytime Heuristic and Monte Carlo Methods for Large-Scale Simultaneous Coalition Structure Generation and Assignment.
Resilient Multi-Agent Reinforcement Learning with Adversarial Value Decomposition.
Time-Independent Planning for Multiple Moving Agents.
Expected Value of Communication for Planning in Ad Hoc Teamwork.
Dec-SGTS: Decentralized Sub-Goal Tree Search for Multi-Agent Coordination.
Lifelong Multi-Agent Path Finding in Large-Scale Warehouses.
Exploration-Exploitation in Multi-Agent Learning: Catastrophe Theory Meets Game Theory.
The Influence of Memory in Multi-Agent Consensus.
Learning to Resolve Conflicts for Multi-Agent Path Finding with Conflict-Based Search.
Scalable and Safe Multi-Agent Motion Planning with Nonlinear Dynamics and Bounded Disturbances.
Inference-Based Deterministic Messaging For Multi-Agent Communication.
Improving Continuous-time Conflict Based Search.
Learning Task-Distribution Reward Shaping with Meta-Learning.
Variational Fair Clustering.
An Efficient Algorithm for Deep Stochastic Contextual Bandits.
Self-correcting Q-learning.
Bias and Variance of Post-processing in Differential Privacy.
Graph Neural Networks with Heterophily.
A Primal-Dual Online Algorithm for Online Matching Problem in Dynamic Environments.
Local Differential Privacy for Bayesian Optimization.
Temporal-Coded Deep Spiking Neural Network with Easy Training and Robust Performance.
Fairness in Forecasting and Learning Linear Dynamical Systems.
Tri-level Robust Clustering Ensemble with Multiple Graph Learning.
Inverse Reinforcement Learning with Natural Language Goals.
Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting.
MetaAugment: Sample-Aware Data Augmentation Policy Learning.
Multi-task Learning by Leveraging the Semantic Information.
How Does the Combined Risk Affect the Performance of Unsupervised Domain Adaptation Approaches?
Fully-Connected Tensor Network Decomposition and Its Application to Higher-Order Tensor Completion.
Going Deeper With Directly-Trained Larger Spiking Neural Networks.
Meta Label Correction for Noisy Label Learning.
Flow-based Generative Models for Learning Manifold to Manifold Mappings.
Improved Consistency Regularization for GANs.
Augmenting Policy Learning with Routines Discovered from a Single Demonstration.
Data Augmentation for Graph Neural Networks.
Efficient Classification with Adaptive KNN.
Exploratory Machine Learning with Unknown Unknowns.
Distilling Localization for Self-Supervised Representation Learning.
Looking Wider for Better Adaptive Representation in Few-Shot Learning.
Exploiting Unlabeled Data via Partial Label Assignment for Multi-Class Semi-Supervised Learning.
Towards Enabling Learnware to Handle Unseen Jobs.
Memory-Gated Recurrent Networks.
Partial-Label and Structure-constrained Deep Coupled Factorization Network.
The Sample Complexity of Teaching by Reinforcement on Q-Learning.
Regret Bounds for Online Kernel Selection in Continuous Kernel Space.
Treatment Effect Estimation with Disentangled Latent Factors.
Deep Wasserstein Graph Discriminant Learning for Graph Classification.
Mean-Variance Policy Iteration for Risk-Averse Reinforcement Learning.
Secure Bilevel Asynchronous Vertical Federated Learning with Backward Updating.
Sample Efficient Reinforcement Learning with REINFORCE.
Interpreting Multivariate Shapley Interactions in DNNs.
Efficient Folded Attention for Medical Image Reconstruction and Segmentation.
Exploration by Maximizing Renyi Entropy for Reward-Free RL Framework.
CloudLSTM: A Recurrent Neural Model for Spatiotemporal Point-cloud Stream Forecasting.
A Hybrid Stochastic Gradient Hamiltonian Monte Carlo Method.
Data-driven Competitive Algorithms for Online Knapsack and Set Cover.
Contrastive Self-supervised Learning for Graph Classification.
Are Adversarial Examples Created Equal? A Learnable Weighted Minimax Risk for Robustness under Non-uniform Attacks.
Curse or Redemption? How Data Heterogeneity Affects the Robustness of Federated Learning.
Knowledge-Guided Object Discovery with Acquired Deep Impressions.
Learning Modality-Specific Representations with Self-Supervised Multi-Task Learning for Multimodal Sentiment Analysis.
Measuring Dependence with Matrix-based Entropy Functional.
Personalized Adaptive Meta Learning for Cold-start User Preference Prediction.
Any-Precision Deep Neural Networks.
DAST: Unsupervised Domain Adaptation in Semantic Segmentation Based on Discriminator Attention and Self-Training.
How Does Data Augmentation Affect Privacy in Machine Learning?
Identity-aware Graph Neural Networks.
Learning Interpretable Models for Coupled Networks Under Domain Constraints.
Image-to-Image Retrieval by Learning Similarity between Scene Graphs.
Enhanced Audio Tagging via Multi- to Single-Modal Teacher-Student Mutual Learning.
Sequential Generative Exploration Model for Partially Observable Reinforcement Learning.
Amata: An Annealing Mechanism for Adversarial Training Acceleration.
Task Cooperation for Semi-Supervised Few-Shot Learning.
Improving Sample Efficiency in Model-Free Reinforcement Learning from Images.
ADAHESSIAN: An Adaptive Second Order Optimizer for Machine Learning.
SeCo: Exploring Sequence Supervision for Unsupervised Representation Learning.
Characterizing the Evasion Attackability of Multi-label Classifiers.
WCSAC: Worst-Case Soft Actor Critic for Safety-Constrained Reinforcement Learning.
Sample Complexity of Policy Gradient Finding Second-Order Stationary Points.
On Convergence of Gradient Expected Sarsa(λ).
FracBits: Mixed Precision Quantization via Fractional Bit-Widths.
Hierarchical Graph Capsule Network.
Robust Bandit Learning with Imperfect Context.
DeHiB: Deep Hidden Backdoor Attack on Semi-supervised Learning via Adversarial Perturbation.
Near Lossless Transfer Learning for Spiking Neural Networks.
Adversarial Partial Multi-Label Learning with Label Disambiguation.
Toward Understanding the Influence of Individual Clients in Federated Learning.
Rethinking Bi-Level Optimization in Neural Architecture Search: A Gibbs Sampling Perspective.
Deep Frequency Principle Towards Understanding Why Deeper Learning Is Faster.
MUFASA: Multimodal Fusion Architecture Search for Electronic Health Records.
Towards Feature Space Adversarial Attack by Style Perturbation.
Towards Generalized Implementation of Wasserstein Distance in GANs.
Learning Graphons via Structured Gromov-Wasserstein Barycenters.
Multi-Task Recurrent Modular Networks.
Isolation Graph Kernel.
Step-Ahead Error Feedback for Distributed Training with Compressed Gradient.
Variational Disentanglement for Rare Event Modeling.
Non-asymptotic Convergence of Adam-type Reinforcement Learning Algorithms under Markovian Sampling.
Domain Adaptation In Reinforcement Learning Via Latent Unified State Representation.
Learning Energy-Based Model with Variational Auto-Encoder as Amortized Sampler.
Learning Cycle-Consistent Cooperative Networks via Alternating MCMC Teaching for Unsupervised Cross-Domain Translation.
Distant Transfer Learning via Deep Random Walk.
Physics-constrained Automatic Feature Engineering for Predictive Modeling in Materials Science.
Communication-Efficient Frank-Wolfe Algorithm for Nonconvex Decentralized Distributed Learning.
Near-Optimal MNL Bandits Under Risk Criteria.
Learning to Purify Noisy Labels via Meta Soft Label Corrector.
Neural Architecture Search as Sparse Supernet.
Fractal Autoencoders for Feature Selection.
Curriculum-Meta Learning for Order-Robust Continual Relation Extraction.
Federated Block Coordinate Descent Scheme for Learning Global and Personalized Models.
Frugal Optimization for Cost-related Hyperparameters.
Fine-grained Generalization Analysis of Vector-Valued Learning.
Fast and Scalable Adversarial Training of Kernel SVM via Doubly Stochastic Gradients.
Training Spiking Neural Networks with Accumulated Spiking Flow.
Self-Supervised Attention-Aware Reinforcement Learning.
Peer Collaborative Learning for Online Knowledge Distillation.
BANANAS: Bayesian Optimization with Neural Architectures for Neural Architecture Search.
Learning Set Functions that are Sparse in Non-Orthogonal Fourier Bases.
Unified Tensor Framework for Incomplete Multi-view Clustering and Missing-view Inferring.
Gene Regulatory Network Inference as Relaxed Graph Matching.
Incremental Embedding Learning via Zero-Shot Translation.
Data-Free Knowledge Distillation with Soft Targeted Transfer Set Synthesis.
Deep Recurrent Belief Propagation Network for POMDPs.
Tied Block Convolution: Leaner and Better CNNs with Shared Thinner Filters.
Harmonized Dense Knowledge Distillation Training for Multi-Exit Architectures.
Adaptive Algorithms for Multi-armed Bandit with Composite and Anonymous Feedback.
Adaptive Verifiable Training Using Pairwise Class Similarity.
Learning with Group Noise.
Tackling Instance-Dependent Label Noise via a Universal Probabilistic Model.
Contrastive Transformation for Self-supervised Correspondence Learning.
Addressing Class Imbalance in Federated Learning.
Adversarial Linear Contextual Bandits with Graph-Structured Side Observations.
Embedding Heterogeneous Networks into Hyperbolic Space Without Meta-path.
Consistency Regularization with High-dimensional Non-adversarial Source-guided Perturbation for Unsupervised Domain Adaptation in Segmentation.
Enhancing Unsupervised Video Representation Learning by Decoupling the Scene and the Motion.
Debiasing Evaluations That Are Biased by Evaluations.
Learning from Noisy Labels with Complementary Loss Functions.
Quantum Exploration Algorithms for Multi-Armed Bandits.
Semi-Supervised Node Classification on Graphs: Markov Random Fields vs. Graph Neural Networks.
Multi-View Information-Bottleneck Representation Learning.
Projection-free Online Learning over Strongly Convex Sets.
Projection-free Online Learning in Dynamic Environments.
Approximate Multiplication of Sparse Matrices with Limited Space.
Contrastive and Generative Graph Convolutional Networks for Graph-based Semi-Supervised Learning.
Nearest Neighbor Classifier Embedded Network for Active Learning.
PID-Based Approach to Adversarial Attacks.
GraphMix: Improved Training of GNNs for Semi-Supervised Learning.
Gated Linear Networks.
Continual General Chunking Problem and SyncMap.
Expected Eligibility Traces.
ESCAPED: Efficient Secure and Private Dot Product Framework for Kernel-based Machine Learning Algorithms with Applications in Healthcare.
Deep Fusion Clustering Network.
Avoiding Kernel Fixed Points: Computing with ELU and GELU Infinite Networks.
Toward Robust Long Range Policy Transfer.
*-CFQ: Analyzing the Scalability of Machine Learning on a Compositional Task.
Learning Adjustment Sets from Observational and Limited Experimental Data.
Differentially Private and Fair Deep Learning: A Lagrangian Dual Approach.
Iterative Bounding MDPs: Learning Interpretable Policies via Non-Interpretable Methods.
Characterizing Deep Gaussian Processes via Nonlinear Recurrence Systems.
Learning Compositional Sparse Gaussian Processes with a Shrinkage Prior.
Meta Learning for Causal Direction.
Towards Trustworthy Predictions from Deep Neural Networks with Fast Adversarial Calibration.
Detecting Adversarial Examples from Sensitivity Inconsistency of Spatial-Transform Domain.
Online Non-Monotone DR-Submodular Maximization.
Semi-Supervised Knowledge Amalgamation for Sequence Classification.
Evolutionary Approach for AutoAugment Using the Thermodynamical Genetic Algorithm.
Gradient Descent Averaging and Primal-dual Averaging for Strongly Convex Optimization.
Foresee then Evaluate: Decomposing Value Estimation with Latent Future Prediction.
Empowering Adaptive Early-Exit Inference with Latency Awareness.
Strategy and Benchmark for Converting Deep Q-Networks to Event-Driven Spiking Neural Networks.
Proxy Graph Matching with Proximal Matching Networks.
Explicitly Modeled Attention Maps for Image Classification.
Near-Optimal Regret Bounds for Contextual Combinatorial Semi-Bandits with Linear Payoff Functions.
Learning Dynamics Models with Stable Invariant Sets.
PAC Learning of Causal Trees with Latent Variables.
TempLe: Learning Template of Transitions for Sample Efficient Multi-task RL.
Stability and Generalization of Decentralized Stochastic Gradient Descent.
HiABP: Hierarchical Initialized ABP for Unsupervised Representation Learning.
'Less Than One'-Shot Learning: Learning N Classes From M < N Samples.
Hierarchical Relational Inference.
Error-Correcting Output Codes with Ensemble Diversity for Robust Learning in Neural Networks.
Implicit Kernel Attention.
Improving Gradient Flow with Unrolled Highway Expectation Maximization.
Solving Common-Payoff Games with Approximate Policy Iteration.
UNIPoint: Universally Approximating Point Processes Intensities.
Differential Spectral Normalization (DSN) for PDE Discovery.
DIBS: Diversity Inducing Information Bottleneck in Model Ensembles.
Towards Domain Invariant Single Image Dehazing.
Interpretable Sequence Classification via Discrete Optimization.
Scalable Affinity Propagation for Massive Datasets.
Online Class-Incremental Continual Learning with Adversarial Shapley Value.
Improved Penalty Method via Doubly Stochastic Gradients for Bilevel Hyperparameter Optimization.
Raven's Progressive Matrices Completion with Latent Gaussian Process Priors.
Federated Multi-Armed Bandits.
Partial Is Better Than All: Revisiting Fine-tuning Strategy for Few-shot Learning.
PDO-eS2CNNs: Partial Differential Operator Based Equivariant Spherical CNNs.
STL-SGD: Speeding Up Local SGD with Stagewise Communication Period.
Time Series Anomaly Detection with Multiresolution Ensemble Decoding.
Theoretically Principled Deep RL Acceleration via Nearest Neighbor Function Approximation.
Membership Privacy for Machine Learning Models Through Knowledge Transfer.
Meta-Learning Effective Exploration Strategies for Contextual Bandits.
Right for Better Reasons: Training Differentiable Models by Constraining their Influence Functions.
Uncertainty-Matching Graph Neural Networks to Defend Against Poisoning Attacks.
Multi-type Disentanglement without Adversarial Training.
Learning Precise Temporal Point Event Detection with Misaligned Labels.
Active Feature Selection for the Mutual Information Criterion.
AdvantageNAS: Efficient Neural Architecture Search with Credit Assignment.
A Deeper Look at the Hessian Eigenspectrum of Deep Neural Networks and its Applications to Regularization.
Inverse Reinforcement Learning with Explicit Policy Estimates.
Anytime Inference with Distilled Hierarchical Neural Ensembles.
Visual Transfer For Reinforcement Learning Via Wasserstein Domain Confusion.
Adversarial Permutation Guided Node Representations for Link Prediction.
Why Adversarial Interaction Creates Non-Homogeneous Patterns: A Pseudo-Reaction-Diffusion Model for Turing Instability.
Shuffling Recurrent Neural Networks.
Robust Fairness Under Covariate Shift.
Multiple Kernel Clustering with Kernel k-Means Coupled Graph Tensor Learning.
Improving Generative Moment Matching Networks with Distribution Partition.
Online DR-Submodular Maximization: Minimizing Regret and Constraint Violation.
Classifying Sequences of Extreme Length with Constant Memory Applied to Malware Detection.
Uncertainty-Aware Policy Optimization: A Robust, Adaptive Trust Region Approach.
Relation-aware Graph Attention Model with Adaptive Self-adversarial Training.
Fast Multi-view Discrete Clustering with Anchor Graphs.
AutoDropout: Learning Dropout Patterns to Regularize Deep Networks.
Fast PCA in 1-D Wasserstein Spaces via B-splines Representation and Metric Projection.
Maximum Roaming Multi-Task Learning.
Vector Quantized Bayesian Neural Network Inference for Data Streams.
Tempered Sigmoid Activations for Deep Learning with Differential Privacy.
Robust Reinforcement Learning: A Case Study in Linear Quadratic Regulation.
NASTransfer: Analyzing Architecture Transferability in Large Scale Neural Architecture Search.
Disentangled Information Bottleneck.
Robustness Guarantees for Mode Estimation with an Application to Bandits.
Defending against Backdoors in Federated Learning with Robust Learning Rate.
Second Order Techniques for Learning Time-series with Structural Breaks.
Augmented Experiment in Material Engineering Using Machine Learning.
Meta-Learning Framework with Applications to Zero-Shot Time-Series Forecasting.
FC-GAGA: Fully Connected Gated Graph Architecture for Spatio-Temporal Traffic Forecasting.
OT-Flow: Fast and Accurate Continuous Normalizing Flows via Optimal Transport.
Learning Deep Generative Models for Queuing Systems.
Multinomial Logit Contextual Bandits: Provable Optimality and Practicality.
Inverse Reinforcement Learning From Like-Minded Teachers.
Warm Starting CMA-ES for Hyperparameter Optimization.
RT3D: Achieving Real-Time Execution of 3D Convolutional Neural Networks on Mobile Devices.
Learning of Structurally Unambiguous Probabilistic Grammars.
Improving Model Robustness by Adaptively Correcting Perturbation Levels with Active Queries.
Precision-based Boosting.
Distributional Reinforcement Learning via Moment Matching.
Top-k Ranking Bayesian Optimization.
An Information-Theoretic Framework for Unifying Active Learning Problems.
Temporal Latent Auto-Encoder: A Method for Probabilistic Multivariate Time Series Forecasting.
Minimum Robust Multi-Submodular Cover for Fairness.
Differentially Private k-Means via Exponential Mechanism and Max Cover.
Modular Graph Transformer Networks for Multi-Label Image Classification.
Clinical Risk Prediction with Temporal Probabilistic Asymmetric Multi-Task Learning.
Advice-Guided Reinforcement Learning in a non-Markovian Environment.
5* Knowledge Graph Embeddings with Projective Transformations.
Objective-Based Hierarchical Clustering of Deep Embedding Vectors.
Game of Gradients: Mitigating Irrelevant Clients in Federated Learning.
Elastic Consistency: A Practical Consistency Model for Distributed Stochastic Gradient Descent.
Task-Agnostic Exploration via Policy Gradient of a Non-Parametric State Entropy Estimate.
Text-based RL Agents with Commonsense Knowledge: New Challenges, Environments and Baselines.
Improved Mutual Information Estimation.
Scheduling of Time-Varying Workloads Using Reinforcement Learning.
A General Class of Transfer Learning Regression without Implementation Cost.
Generative Semi-supervised Learning for Multivariate Time Series Imputation.
Discovering Fully Oriented Causal Networks.
Consistency and Finite Sample Behavior of Binary Class Probability Estimation.
Policy Optimization as Online Learning with Mediator Feedback.
Lenient Regret for Multi-Armed Bandits.
Physarum Powered Differentiable Linear Programming Layers and Applications.
Exacerbating Algorithmic Bias through Fairness Attacks.
Infinite Gaussian Mixture Modeling with an Improved Estimation of the Number of Clusters.
Scalable Graph Networks for Particle Simulations.
Searching for Machine Learning Pipelines Using a Context-Free Grammar.
Deep Mutual Information Maximin for Cross-Modal Clustering.
Composite Adversarial Attacks.
Exact Reduction of Huge Action Spaces in General Reinforcement Learning.
Sequential Attacks on Kalman Filter-based Forward Collision Warning Systems.
Unsupervised Learning of Graph Hierarchical Abstractions with Differentiable Coarsening and Optimal Transport.
Joint-Label Learning by Dual Augmentation for Time Series Classification.
Learning Representations for Incomplete Time Series Clustering.
On the Adequacy of Untuned Warmup for Adaptive Optimization.
Multi-Domain Multi-Task Rehearsal for Lifelong Learning.
Adaptive Knowledge Driven Regularization for Deep Neural Networks.
Semi-supervised Medical Image Segmentation through Dual-task Consistency.
Revisiting Co-Occurring Directions: Sharper Analysis and Efficient Algorithm for Sparse Matrices.
PULNS: Positive-Unlabeled Learning with Effective Negative Sample Selector.
Tailoring Embedding Function to Heterogeneous Few-Shot Tasks by Global and Local Feature Adaptors.
Decentralized Policy Gradient Descent Ascent for Safe Multi-Agent Reinforcement Learning.
Stochastic Bandits with Graph Feedback in Non-Stationary Environments.
Stochastic Graphical Bandits with Adversarial Corruptions.
Improving Causal Discovery By Optimal Bayesian Network Learning.
Learning from eXtreme Bandit Feedback.
Task Aligned Generative Meta-learning for Zero-shot Learning.
ROSITA: Refined BERT cOmpreSsion with InTegrAted techniques.
Train a One-Million-Way Instance Classifier for Unsupervised Visual Representation Learning.
Post-training Quantization with Multiple Points: Mixed Precision without Mixed Precision.
FLAME: Differentially Private Federated Learning in the Shuffle Model.
Dynamically Grown Generative Adversarial Networks.
Hierarchical Multiple Kernel Clustering.
Stable Adversarial Learning under Distributional Shifts.
Overcoming Catastrophic Forgetting in Graph Neural Networks.
Unchain the Search Space with Hierarchical Differentiable Architecture Search.
Learning a Few-shot Embedding Model with Contrastive Learning.
TransTailor: Pruning the Pre-trained Model for Improved Transfer Learning.
Multi-Proxy Wasserstein Classifier for Image Classification.
Auto-Encoding Transformations in Reparameterized Lie Groups for Unsupervised Learning.
Class-Attentive Diffusion Network for Semi-Supervised Classification.
Sample Selection for Universal Domain Adaptation.
From Label Smoothing to Label Relaxation.
Doubly Residual Neural Decoder: Towards Low-Complexity High-Performance Channel Decoding.
Large Norms of CNN Layers Do Not Hurt Adversarial Robustness.
Longitudinal Deep Kernel Gaussian Process Regression.
Contrastive Clustering.
TRQ: Ternary Neural Networks With Residual Quantization.
Online Optimal Control with Affine Constraints.
Scheduled Sampling in Vision-Language Pretraining with Decoupled Encoder-Decoder Network.
One-shot Graph Neural Architecture Search with Dynamic Search Space.
Learned Extragradient ISTA with Interpretable Residual Structures for Sparse Coding.
MFES-HB: Efficient Hyperband with Multi-Fidelity Quality Measurements.
Improving Adversarial Robustness via Probabilistically Compact Loss with Logit Constraints.
A Free Lunch for Unsupervised Domain Adaptive Object Detection without Source Data.
Sublinear Classical and Quantum Algorithms for General Matrix Games.
Bi-Classifier Determinacy Maximization for Unsupervised Domain Adaptation.
Multi-View Representation Learning with Manifold Smoothness.
Learning Graph Neural Networks with Approximate Gradient Descent.
Bayesian Distributional Policy Gradients.
Synergetic Learning of Heterogeneous Temporal Sequences for Multi-Horizon Probabilistic Forecasting.
Token-Aware Virtual Adversarial Training in Natural Language Understanding.
Learning Intact Features by Erasing-Inpainting for Few-shot Classification.
Self-Paced Two-dimensional PCA.
A Bayesian Approach for Subset Selection in Contextual Bandits.
ShapeNet: A Shapelet-Neural Network Approach for Multivariate Time Series Classification.
High Fidelity GAN Inversion via Prior Multi-Subspace Feature Composition.
VSQL: Variational Shadow Quantum Learning for Classification.
GoT: a Growing Tree Model for Clustering Ensemble.
LRSC: Learning Representations for Subspace Clustering.
Unsupervised Active Learning via Subspace Learning.
Enhancing Parameter-Free Frank Wolfe with an Extra Subproblem.
Memory and Computation-Efficient Kernel SVM via Binary Embedding and Ternary Model Coefficients.
Unsupervised Domain Adaptation for Semantic Segmentation by Content Transfer.
Interpretable Embedding Procedure Knowledge Transfer via Stacked Principal Component Analysis and Graph Neural Network.
Learnable Dynamic Temporal Pooling for Time Series Classification.
Norm-Based Generalisation Bounds for Deep Multi-Class Convolutional Neural Networks.
Lipschitz Lifelong Reinforcement Learning.
Metrics and Continuity in Reinforcement Learning.
Query Training: Learning a Worse Model to Infer Better Marginals in Undirected Graphical Models with Hidden Variables.
Hypothesis Disparity Regularized Mutual Information Maximization.
Compressing Deep Convolutional Neural Networks by Stacking Low-dimensional Binary Convolution Filters.
MolGrow: A Graph Normalizing Flow for Hierarchical Molecular Generation.
Positions, Channels, and Layers: Fully Generalized Non-Local Network for Singer Identification.
Asynchronous Optimization Methods for Efficient Training of Deep Neural Networks with Guarantees.
Nearly Linear-Time, Parallelizable Algorithms for Non-Monotone Submodular Maximization.
HINT: Hierarchical Invertible Neural Transport for Density Estimation and Bayesian Inference.
Sparsity Aware Normalization for GANs.
Visual Concept Reasoning Networks.
Neural Sequence-to-grid Module for Learning Symbolic Rules.
Kernel-convoluted Deep Neural Networks with Data Augmentation.
DPM: A Novel Training Method for Physics-Informed Neural Networks in Extrapolation.
Split-and-Bridge: Adaptable Class Incremental Learning within a Single Neural Network.
Counterfactual Fairness with Disentangled Causal Effect Variational Autoencoder.
Understanding Catastrophic Overfitting in Single-step Adversarial Training.
GLISTER: Generalization based Data Subset Selection for Efficient and Robust Learning.
A Flexible Framework for Communication-Efficient Machine Learning.
Improving Fairness and Privacy in Selection Problems.
Bayesian Dynamic Mode Decomposition with Variational Matrix Factorization.
A Recipe for Global Convergence Guarantee in Deep Neural Networks.
Learning Generalized Relational Heuristic Networks for Model-Agnostic Planning.
Deep Probabilistic Canonical Correlation Analysis.
Exploration via State influence Modeling.
Winning Lottery Tickets in Deep Generative Models.
A Sample-Efficient Algorithm for Episodic Finite-Horizon MDP with Constraints.
Linearly Replaceable Filters for Deep Network Channel Pruning.
Balanced Open Set Domain Adaptation via Centroid Alignment.
Power up! Robust Graph Convolutional Network via Graph Powering.
Temporal-Logic-Based Reward Shaping for Continuing Reinforcement Learning Tasks.
LightXML: Transformer with Dynamic Negative Sampling for High-Performance Extreme Multi-label Text Classification.
Action Candidate Based Clipped Double Q-learning for Discrete and Continuous Action Tasks.
Clustering Ensemble Meets Low-rank Tensor Approximation.
Intrinsic Certified Robustness of Bagging against Data Poisoning Attacks.
Dynamic Multi-Context Attention Networks for Citation Forecasting of Scientific Publications.
Show, Attend and Distill: Knowledge Distillation via Attention-based Feature Matching.
Active Bayesian Assessment of Black-Box Classifiers.
IB-GAN: Disentangled Representation Learning with Information Bottleneck Generative Adversarial Networks.
Neural Utility Functions.
Constructing a Fair Classifier with Generated Fair Data.
Variance Penalized On-Policy and Off-Policy Actor-Critic.
Accurate and Robust Feature Importance Estimation under Distribution Shifts.
Large Batch Optimization for Deep Learning Using New Complete Layer-Wise Adaptive Rate Scaling.
Reward-Biased Maximum Likelihood Estimation for Linear Stochastic Bandits.
Personalized Cross-Silo Federated Learning on Non-IID Data.
ACMo: Angle-Calibrated Moment Methods for Stochastic Optimization.
Learning to Reweight Imaginary Transitions for Model-Based Reinforcement Learning.
Attributes-Guided and Pure-Visual Attention Alignment for Few-Shot Recognition.
Accelerating Continuous Normalizing Flow with Trajectory Polynomial Regularization.
Adversarial Defence by Diversified Simultaneous Training of Deep Ensembles.
Multidimensional Uncertainty-Aware Evidential Neural Networks.
Predictive Adversarial Learning from Positive and Unlabeled Data.
Continual Learning by Using Information of Each Class Holistically.
Multi-scale Graph Fusion for Co-saliency Detection.
OPQ: Compressing Deep Neural Networks with One-shot Pruning-Quantization.
Boosting Multi-task Learning Through Combination of Task Labels - with Applications in ECG Phenotyping.
Gaussian Process Priors for View-Aware Inference.
Disentangled Representation Learning in Heterogeneous Information Network for Large-scale Android Malware Detection in the COVID-19 Era and Beyond.
Slimmable Generative Adversarial Networks.
Reinforcement Learning Based Multi-Agent Resilient Control: From Deep Neural Networks to an Adaptive Law.
Storage Fit Learning with Feature Evolvable Streams.
Topology Distance: A Topology-Based Approach for Evaluating Generative Adversarial Networks.
Graph Game Embedding.
Learning Model-Based Privacy Protection under Budget Constraints.
Scaling-Up Robust Gradient Descent Techniques.
Provably Good Solutions to the Knapsack Problem via Neural Networks of Bounded Size.
Analysing the Noise Model Error for Realistic Noisy Label Data.
Learning with Safety Constraints: Sample Complexity of Reinforcement Learning for Constrained MDPs.
Liquid Time-constant Networks.
DeepSynth: Automata Synthesis for Automatic Task Segmentation in Deep Reinforcement Learning.
Explanation Consistency Training: Facilitating Consistency-Based Semi-Supervised Learning with Interpretability.
High-Dimensional Bayesian Optimization via Tree-Structured Additive Models.
Towards Reusable Network Components by Learning Compatible Representations.
Controllable Guarantees for Fair Outcomes via Contrastive Information Estimation.
Revisiting Iterative Back-Translation from the Perspective of Compositional Generalization.
Attentive Neural Point Processes for Event Forecasting.
Efficient On-Chip Learning for Optical Neural Networks Through Power-Aware Sparse Zeroth-Order Optimization.
Attribute-Guided Adversarial Training for Robustness to Natural Perturbations.
The Importance of Modeling Data Missingness in Algorithmic Fairness: A Causal Perspective.
Justicia: A Stochastic SAT Approach to Formally Verify Fairness.
Uncertainty-Aware Multi-View Representation Learning.
Increasing Iterate Averaging for Solving Saddle-Point Problems.
Addressing Domain Gap via Content Invariant Representation for Semantic Segmentation.
A Trace-restricted Kronecker-Factored Approximation to Natural Gradient.
On the Convergence of Communication-Efficient Local SGD for Federated Learning.
Stabilizing Q Learning Via Soft Mellowmax Operator.
Diffusion Network Inference from Partial Observations.
HiGAN: Handwriting Imitation Conditioned on Arbitrary-Length Texts and Disentangled Styles.
Generalize a Small Pre-trained Model to Arbitrarily Large TSP Instances.
Agreement-Discrepancy-Selection: Active Learning with Progressive Distribution Alignment.
Towards Effective Context for Meta-Reinforcement Learning: an Approach based on Contrastive Learning.
Few-Shot One-Class Classification via Meta-Learning.
Practical and Rigorous Uncertainty Bounds for Gaussian Process Regression.
Collaborative Group Learning.
Learning to Augment for Data-scarce Domain BERT Knowledge Distillation.
SHOT-VAE: Semi-supervised Deep Generative Models With Label-aware ELBO Approximations.
UAG: Uncertainty-aware Attention Graph Neural Network for Defending Adversarial Attacks.
Deep Switching Auto-Regressive Factorization: Application to Time Series Forecasting.
Learning to Reweight with Deep Interactions.
Learning a Gradient-free Riemannian Optimizer on Tangent Spaces.
Adversarial Training and Provable Robustness: A Tale of Two Objectives.
Deep Graph Spectral Evolution Networks for Graph Topological Evolution.
Almost Linear Time Density Level Set Estimation via DBSCAN.
Regret Bounds for Batched Bandits.
Learning to Cascade: Confidence Calibration for Improving the Accuracy and Computational Cost of Cascade Inference Systems.
Projection-Free Bandit Optimization with Privacy Guarantees.
Adaptive Gradient Methods for Constrained Convex Optimization and Variational Inequalities.
Learning Prediction Intervals for Model Performance.
The Parameterized Complexity of Clustering Incomplete Data.
Reinforcement Learning with Trajectory Feedback.
Semi-Supervised Metric Learning: A Deep Resurrection.
Knowledge Refactoring for Inductive Program Synthesis.
Combinatorial Pure Exploration with Full-Bandit or Partial Linear Feedback.
A One-Size-Fits-All Solution to Conservative Bandit Problems.
Residual Shuffle-Exchange Networks for Fast Processing of Long Sequences.
Semi-Supervised Learning with Variational Bayesian Inference and Maximum Uncertainty Regularization.
Knowledge Refinery: Learning from Decoupled Label.
Differentially Private and Communication Efficient Collaborative Learning.
Mercer Features for Efficient Combinatorial Bayesian Optimization.
Learning with Retrospection.
Sample-Efficient L0-L2 Constrained Structure Learning of Sparse Ising Models.
Generalized Adversarially Learned Inference.
Differentially Private Stochastic Coordinate Descent.
Loop Estimator for Discounted Values in Markov Reward Processes.
The Value-Improvement Path: Towards Better Representations for Reinforcement Learning.
Type-augmented Relation Prediction in Knowledge Graphs.
Cost-aware Graph Generation: A Deep Bayesian Optimization Approach.
Computationally Tractable Riemannian Manifolds for Graph Embeddings.
Transfer Learning for Efficient Iterative Safety Validation.
Continuous-Time Attention for Sequential Learning.
Self-Progressing Robust Training.
Neighborhood Consensus Networks for Unsupervised Multi-view Outlier Detection.
NASGEM: Neural Architecture Search via Graph Embedding Method.
HyDRA: Hypergradient Data Relevance Analysis for Interpreting Deep Neural Networks.
Deep Spiking Neural Network with Neural Oscillation and Spike-Phase Information.
Fitting the Search Space of Weight-sharing NAS with Graph Convolutional Networks.
Neural Relational Inference with Efficient Message Passing Mechanisms.
THOR, Trace-based Hardware-driven Layer-Oriented Natural Gradient Descent Computation.
Distributed Ranking with Communications: Approximation Analysis and Applications.
Cross-Layer Distillation with Semantic Calibration.
Addressing Action Oscillations through Learning Policy Inertia.
Scalable and Explainable 1-Bit Matrix Completion via Graph Signal Learning.
Deep Verifier Networks: Verification of Deep Discriminative Models with Deep Generative Models.
Using Hindsight to Anchor Past Knowledge in Continual Learning.
Differentially Private Decomposable Submodular Maximization.
Provable Benefits of Overparameterization in Model Compression: From Double Descent to Pruning Neural Networks.
On Online Optimization: Dynamic Regret Analysis of Strongly Convex and Smooth Problems.
Extending Multi-Sense Word Embedding to Phrases and Sentences for Unsupervised Semantic Applications.
A Multi-step-ahead Markov Conditional Forward Model with Cube Perturbations for Extreme Weather Forecasting.
High-Confidence Off-Policy (or Counterfactual) Variance Estimation.
Automated Clustering of High-dimensional Data with a Feature Weighted Mean Shift Algorithm.
Frivolous Units: Wider Networks Are Not Really That Wide.
Curriculum Labeling: Revisiting Pseudo-Labeling for Semi-Supervised Learning.
Counterfactual Explanations for Oblique Decision Trees: Exact, Efficient Algorithms.
Dual Quaternion Knowledge Graph Embeddings.
Provably Secure Federated Learning against Malicious Clients.
Open-Set Recognition with Gaussian Mixture Variational Autoencoders.
A Blind Block Term Decomposition of High Order Tensors.
Time Series Domain Adaptation via Sparse Associative Structure Alignment.
Exploiting Diverse Characteristics and Adversarial Ambivalence for Domain Adaptive Segmentation.
Cascade Size Distributions: Why They Matter and How to Compute Them Efficiently.
Improving Ensemble Robustness by Collaboratively Promoting and Demoting Adversarial Robustness.
Fairness, Semi-Supervised Learning, and More: A General Framework for Clustering with Stochastic Pairwise Constraints.
Sample-Specific Output Constraints for Neural Networks.
Fast Training of Provably Robust Neural Networks by SingleProp.
Stochastic Precision Ensemble: Self-Knowledge Distillation for Quantized Deep Neural Networks.
Communication-Aware Collaborative Learning.
Understanding Decoupled and Early Weight Decay.
Characterizing the Loss Landscape in Non-Negative Matrix Factorization.
Ordinal Historical Dependence in Graphical Event Models with Tree Representations.
ExGAN: Adversarial Generation of Extreme Samples.
A Theory of Independent Mechanisms for Extrapolation in Generative Models.
Relative Variational Intrinsic Control.
Deterministic Mini-batch Sequencing for Training Deep Neural Networks.
Correlative Channel-Aware Fusion for Multi-View Time Series Classification.
DecAug: Out-of-Distribution Generalization via Decomposed Feature Representation and Semantic Augmentation.
Deep Radial-Basis Value Functions for Continuous Control.
Robust Model Compression Using Deep Hypotheses.
TabNet: Attentive Interpretable Tabular Learning.
The Tractability of SHAP-Score-Based Explanations for Classification over Deterministic and Decomposable Boolean Circuits.
On Lipschitz Regularization of Convolutional Layers using Toeplitz Matrix Theory.
An Enhanced Advising Model in Teacher-Student Framework using State Categorization.
Noise Estimation Using Density Estimation for Self-Supervised Multimodal Learning.
Computing an Efficient Exploration Basis for Learning with Univariate Polynomial Features.
Decentralized Multi-Agent Linear Bandits with Safety Constraints.
Does Explainable Artificial Intelligence Improve Human Decision-Making?
eTREE: Learning Tree-structured Embeddings.
Deep Bayesian Quadrature Policy Optimization.
Learned Bi-Resolution Image Coding using Generalized Octave Convolutions.
Learning Invariant Representations using Inverse Contrastive Loss.
Semi-supervised Sequence Classification through Change Point Detection.
Improved Worst-Case Regret Bounds for Randomized Least-Squares Value Iteration.
DART: Adaptive Accept Reject Algorithm for Non-Linear Combinatorial Bandits.
SWIFT: Scalable Wasserstein Factorization for Sparse Nonnegative Tensors.
Testing Independence Between Linear Combinations for Causal Discovery.
On-the-fly Synthesis for LTL over Finite Traces.
Focused Inference and System P.
On Exploiting Hitting Sets for Model Reconciliation.
On the Tractability of SHAP Explanations.
Strong Explanations in Abstract Argumentation.
Stratified Negation in Datalog with Metric Temporal Operators.
Quantification of Resource Production Incompleteness.
ChronoR: Rotation Based Temporal Knowledge Graph Embedding.
Interpreting Neural Networks as Quantitative Argumentation Frameworks.
Parameterized Complexity of Small Decision Tree Learning.
GENSYNTH: Synthesizing Datalog Programs without Language Bias.
Ranking Sets of Defeasible Elements in Preferential Approaches to Structured Argumentation: Postulates, Relations, and Characterizations.
Parameterized Complexity of Logic-Based Argumentation in Schaefer's Framework.
KG-BART: Knowledge Graph-Augmented BART for Generative Commonsense Reasoning.
Learning Term Embeddings for Lexical Taxonomies.
Parameterized Logical Theories.
Commonsense Knowledge Augmentation for Low-Resource Languages via Adversarial Learning.
(Comet-) Atomic 2020: On Symbolic and Neural Commonsense Knowledge Graphs.
REM-Net: Recursive Erasure Memory Network for Commonsense Evidence Refinement.
Mining EL Bases with Adaptable Role Depth.
Constraint Logic Programming for Real-World Test Laboratory Scheduling.
Knowledge-Base Degrees of Inconsistency: Complexity and Counting.
Answering Regular Path Queries Under Approximate Semantics in Lightweight Description Logics.
A Simple Framework for Cognitive Planning.
SMT-based Safety Checking of Parameterized Multi-Agent Systems.
Treewidth-Aware Complexity in ASP: Not all Positive Cycles are Equally Hard.
On the Complexity of Sum-of-Products Problems over Semirings.
The Complexity Landscape of Claim-Augmented Argumentation Frameworks.
Recursion in Abstract Argumentation is Hard - On the Complexity of Semantics Based on Weak Admissibility.
A Deep Reinforcement Learning Approach to First-Order Logic Theorem Proving.
Topology-Aware Correlations Between Relations for Inductive Link Prediction in Knowledge Graphs.
Preferred Explanations for Ontology-Mediated Queries under Existential Rules.
Contextual Conditional Reasoning.
Certifying Top-Down Decision-DNNF Compilers.
Algebra of Modular Systems: Containment and Equivalence.
Conditional Inference under Disjunctive Rationality.
Network Satisfaction for Symmetric Relation Algebras with a Flexible Atom.
The Counterfactual NESS Definition of Causation.
Equivalent Causal Models.
Living Without Beth and Craig: Definitions and Interpolants in Description Logics with Nominals and Role Inclusions.
A General Setting for Gradual Semantics Dealing with Similarity.
Argumentation Frameworks with Strong and Weak Constraints: Semantics and Complexity.
VMLoc: Variational Fusion For Learning-Based Multimodal Camera Localization.
Generative Partial Visual-Tactile Fused Object Clustering.
CMAX++ : Leveraging Experience in Planning and Execution using Inaccurate Models.
Differentiable Fluids with Solid Coupling for Learning and Control.
IDOL: Inertial Deep Orientation-Estimation and Localization.
SCAN: A Spatial Context Attentive Network for Joint Multi-Agent Intent Prediction.
Learning Intuitive Physics with Multimodal Generative Models.
DenserNet: Weakly Supervised Visual Localization Using Multi-Scale Feature Aggregation.
Supervised Training of Dense Object Nets using Optimal Descriptors for Industrial Robotic Applications.
Consistent Right-Invariant Fixed-Lag Smoother with Application to Visual Inertial SLAM.
Enabling Fast Instruction-Based Modification of Learned Robot Skills.
I3DOL: Incremental 3D Object Learning without Catastrophic Forgetting.
BT Expansion: a Sound and Complete Algorithm for Behavior Planning of Intelligent Robots with Behavior Trees.
Automatic Generation of Flexible Plans via Diverse Temporal Planning.
Inferring Emotion from Large-scale Internet Voice Data: A Semi-supervised Curriculum Augmentation based Deep Learning Approach.
A Continual Learning Framework for Uncertainty-Aware Interactive Image Segmentation.
Content Learning with Structure-Aware Writing: A Graph-Infused Dual Conditional Variational Autoencoder for Automatic Storytelling.
Bounded Risk-Sensitive Markov Games: Forward Policy Design and Inverse Reward Learning with Iterative Reasoning and Cumulative Prospect Theory.
Learning Rewards From Linguistic Feedback.
Uncertain Graph Neural Networks for Facial Action Unit Detection.
Narrative Plan Generation with Self-Supervised Learning.
Indecision Modeling.
Improving the Performance-Compatibility Tradeoff with Personalized Objective Functions.
AI-Assisted Scientific Data Collection with Iterative Human Feedback.
Contrastive Adversarial Learning for Person Independent Facial Emotion Recognition.
Goal Blending for Responsive Shared Autonomy in a Navigating Vehicle.
ActionBert: Leveraging User Actions for Semantic Understanding of User Interfaces.
Illuminating Mario Scenes in the Latent Space of a Generative Adversarial Network.
Wasserstein Distributionally Robust Inverse Multiobjective Optimization.
Classification Under Human Assistance.
User Driven Model Adjustment via Boolean Rule Explanations.
Learning to Sit: Synthesizing Human-Chair Interactions via Hierarchical Control.
Human Uncertainty Inference via Deterministic Ensemble Neural Networks.
MARTA: Leveraging Human Rationales for Explainable Text Classification.
Automated Storytelling via Causal, Commonsense Plot Ordering.
Teaching Active Human Learners.
Time to Transfer: Predicting and Evaluating Machine-Human Chatting Handoff.
Learning from Crowds by Modeling Common Confusions.
Power in Liquid Democracy.
Computing Ex Ante Coordinated Team-Maxmin Equilibria in Zero-Sum Multiplayer Extensive-Form Games.
Classification with Few Tests through Self-Selection.
Incentive-Aware PAC Learning.
Automated Mechanism Design for Classification with Partial Verification.
Finding and Certifying (Near-)Optimal Strategies in Black-Box Extensive-Form Games.
Targeted Negative Campaigning: Complexity and Approximations.
A Model of Winners Allocation.
If You Like Shapley Then You'll Love the Core.
The Smoothed Complexity of Computing Kemeny and Slater Rankings.
Facility's Perspective to Fair Facility Location Problems.
Restricted Domains of Dichotomous Preferences with Possibly Incomplete Information.
Coupon Design in Advertising Systems.
Modeling Voters in Multi-Winner Approval Voting.
Solution Concepts in Hierarchical Games Under Bounded Rationality With Applications to Autonomous Driving.
The Maximin Support Method: An Extension of the D'Hondt Method to Approval-Based Multiwinner Elections.
Online Posted Pricing with Unknown Time-Discounted Valuations.
Estimating α-Rank by Maximizing Information Gain.
A Permutation-Equivariant Neural Network Architecture For Auction Design.
Market-Based Explanations of Collective Decisions.
Preference Elicitation as Average-Case Sorting.
From Behavioral Theories to Econometrics: Inferring Preferences of Human Agents from Data on Repeated Interactions.
Scarce Societal Resource Allocation and the Price of (Local) Justice.
Fair and Efficient Allocations with Limited Demands.
Majority Opinion Diffusion in Social Networks: An Adversarial Approach.
Coalition Formation in Multi-defender Security Games.
On Fair and Efficient Allocations of Indivisible Goods.
Hindsight and Sequential Rationality of Correlated Play.
Complexity and Algorithms for Exploiting Quantal Opponents in Large Two-Player Games.
Trembling-Hand Perfection and Correlation in Sequential Games.
On the Approximation of Nash Equilibria in Sparse Win-Lose Multi-player Games.
Budget Feasible Mechanisms Over Graphs.
Safe Search for Stackelberg Equilibria in Extensive-Form Games.
Evolution Strategies for Approximate Solution of Bayesian Games.
On the PTAS for Maximin Shares in an Indivisible Mixed Manna.
Classification with Strategically Withheld Data.
Multi-Party Campaigning.
Multi-Scale Games: Representing and Solving Games on Networks with Group Structure.
Computing the Proportional Veto Core.
Necessarily Optimal One-Sided Matchings.
Fair and Efficient Allocations under Lexicographic Preferences.
District-Fair Participatory Budgeting.
Aggregating Binary Judgments Ranked by Accuracy.
An Analysis of Approval-Based Committee Rules for 2D-Euclidean Elections.
Fair and Efficient Online Allocations with Normalized Valuations.
Infinite-Dimensional Fisher Markets: Equilibrium, Duality and Optimization.
Efficient Truthful Scheduling and Resource Allocation through Monitoring.
Present-Biased Optimization.
Condorcet Relaxation In Spatial Voting.
Convergence Analysis of No-Regret Bidding Algorithms in Repeated Auctions.
Simultaneous 2nd Price Item Auctions with No-Underbidding.
Model-Free Online Learning in Unknown Sequential Decision Making Problems and Games.
Bandit Linear Optimization for Sequential Decision Making and Extensive-Form Games.
Faster Game Solving via Predictive Blackwell Approachability: Connecting Regret Matching and Mirror Descent.
Almost Envy-freeness, Envy-rank, and Nash Social Welfare Matchings.
Incentivizing Truthfulness Through Audits in Strategic Classification.
United for Change: Deliberative Coalition Formation to Change the Status Quo.
Mind the Gap: Cake Cutting With Separation.
PoA of Simple Auctions with Interdependent Values.
On Fair Division under Heterogeneous Matroid Constraints.
Model-sharing Games: Analyzing Federated Learning Under Voluntary Participation.
Computational Analyses of the Electoral College: Campaigning Is Hard But Approximately Manageable.
Proportional Representation under Single-Crossing Preferences Revisited.
Scalable Equilibrium Computation in Multi-agent Influence Games on Networks.
Fair and Efficient Allocations under Subadditive Valuations.
Computing Quantal Stackelberg Equilibrium in Extensive-Form Games.
Signaling in Bayesian Network Congestion Games: the Subtle Power of Symmetry.
Persuading Voters in District-based Elections.
Welfare Guarantees in Schelling Segregation.
Margin of Victory in Tournaments: Structural and Experimental Results.
Reinforcement Learning of Sequential Price Mechanisms.
Reaching Individually Stable Coalition Structures in Hedonic Games.
Preserving Condorcet Winners under Strategic Manipulation.
On the Complexity of Finding Justifications for Collective Decisions.
Selfish Creation of Social Networks.
Protecting the Protected Group: Circumventing Harmful Fairness.
Maximin Fairness with Mixed Divisible and Indivisible Goods.
Dividing a Graphical Cake.
The Price of Connectivity in Fair Division.
Achieving Proportionality up to the Maximin Item with Indivisible Goods.
Defending against Contagious Attacks on a Network with Resource Reallocation.
Bayesian Persuasion under Ex Ante and Ex Post Constraints.
Fair and Truthful Mechanisms for Dichotomous Valuations.
Proportionally Representative Participatory Budgeting with Ordinal Preferences.
Achieving Envy-freeness and Equitability with Monetary Transfers.
Forming Better Stable Solutions in Group Formation Games Inspired by Internet Exchange Points (IXPs).
Representative Proxy Voting.
A Few Queries Go a Long Way: Information-Distortion Tradeoffs in Matching.
Double Oracle Algorithm for Computing Equilibria in Continuous Games.
Adaptive Teaching of Temporal Logic Formulas to Preference-based Learners.
Neural-Symbolic Integration: A Compositional Perspective.
Encoding Human Domain Knowledge to Warm Start Reinforcement Learning.
Differentiable Inductive Logic Programming for Structured Examples.
Classification by Attention: Scene Graph Classification with Prior Knowledge.
A Unified Framework for Planning with Learned Neural Network Transition Models.
Recognizing and Verifying Mathematical Equations using Multiplicative Differential Neural Units.
A Scalable Reasoning and Learning Approach for Neural-Symbolic Stream Fusion.
Explaining Neural Matrix Factorization with Gradient Rollback.
Self-Supervised Self-Supervision by Combining Deep Learning and Probabilistic Logic.
Answering Complex Queries in Knowledge Graphs with Bidirectional Sequence Encoders.
Learning by Fixing: Solving Math Word Problems with Weak Supervision.
Learning Game-Theoretic Models of Multiagent Trajectories Using Implicit Layers.
Planning from Pixels in Atari with Learned Symbolic Representations.
Aligning Artificial Neural Networks and Ontologies towards Explainable AI.
Dynamic Neuro-Symbolic Knowledge Graph Construction for Zero-shot Commonsense Question Answering.
Interpretable Actions: Controlling Experts with Understandable Commands.
Conversational Neuro-Symbolic Commonsense Reasoning.
C-Watcher: A Framework for Early Detection of High-Risk Neighborhoods Ahead of COVID-19 Outbreak.
Tracking Disease Outbreaks from Sparse Data with Bayesian Inference.
Context Matters: Graph-based Self-supervised Representation Learning for Medical Images.
Gaining Insight into SARS-CoV-2 Infection and COVID-19 Severity Using Self-supervised Edge Features and Graph Neural Networks.
Steering a Historical Disease Forecasting Model Under a Pandemic: Case of Flu and COVID-19.
MiniSeg: An Extremely Minimum Network for Efficient COVID-19 Segmentation.
Transfer Graph Neural Networks for Pandemic Forecasting.
STELAR: Spatio-temporal Tensor Factorization with Latent Epidemiological Regularization.
Automated Model Design and Benchmarking of Deep Learning Models for COVID-19 Detection with Chest CT Scans.
Persistence of Anti-vaccine Sentiment in Social Networks Through Strategic Interactions.
Savable but Lost Lives when ICU Is Overloaded: a Model from 733 Patients in Epicenter Wuhan, China.
Catch Me if I Can: Detecting Strategic Behaviour in Peer Assessment.
A Novice-Reviewer Experiment to Address Scarcity of Qualified Reviewers in Large Conferences.
A Market-Inspired Bidding Scheme for Peer Review Paper Assignment.
Uncovering Latent Biases in Text: Method and Application to Peer Review.
Argument Mining Driven Analysis of Peer-Reviews.
Relation-Aware Neighborhood Matching Model for Entity Alignment.
Adversarial Directed Graph Embedding.
Learning from History: Modeling Temporal Knowledge Graphs with Sequential Copy-Generation Networks.
Modeling Heterogeneous Relations across Multiple Modes for Potential Crowd Flow Prediction.
Overcoming Catastrophic Forgetting in Graph Neural Networks with Experience Replay.
Cold-start Sequential Recommendation via Meta Learner.
Heterogeneous Graph Structure Learning for Graph Neural Networks.
A Graph-based Relevance Matching Model for Ad-hoc Retrieval.
Generalized Relation Learning with Semantic Correlation Awareness for Link Prediction.
Tripartite Collaborative Filtering with Observability and Selection for Debiasing Rating Estimation on Missing-Not-at-Random Data.
Taxonomy Completion via Triplet Matching Network.
AugSplicing: Synchronized Behavior Detection in Streaming Tensors.
Self-Supervised Prototype Representation Learning for Event-Based Corporate Profiling.
Dual Sparse Attention Network For Session-based Recommendation.
Deep Graph-neighbor Coherence Preserving Network for Unsupervised Cross-modal Hashing.
Coupled Layer-wise Graph Convolution for Transportation Demand Prediction.
Interpretable Clustering on Dynamic Graphs with Recurrent Graph Neural Networks.
Relaxed Clustered Hawkes Process for Student Procrastination Modeling in MOOCs.
Why Do Attributes Propagate in Graph Convolutional Neural Networks?
Capturing Delayed Feedback in Conversion Rate Prediction via Elapsed-Time Sampling.
Rethinking Graph Regularization for Graph Neural Networks.
Dynamic Knowledge Graph Alignment.
A Unified Pretraining Framework for Passage Ranking and Expansion.
Transformer-Style Relational Reasoning with Dynamic Memory Updating for Temporal Network Modeling.
Towards Consumer Loan Fraud Detection: Graph Neural Networks with Role-Constrained Conditional Random Field.
Out-of-Town Recommendation with Travel Intention Modeling.
Hierarchical Reinforcement Learning for Integrated Recommendation.
A General Offline Reinforcement Learning Framework for Interactive Recommendation.
Self-Supervised Hypergraph Convolutional Networks for Session-based Recommendation.
AttnMove: History Enhanced Trajectory Recovery via Attentional Network.
Knowledge-Enhanced Hierarchical Graph Transformer Network for Multi-Behavior Recommendation.
Inductive Graph Neural Networks for Spatiotemporal Kriging.
Hybrid-order Stochastic Block Model.
Fairness-aware News Recommendation with Decomposed Adversarial Learning.
Learning to Truncate Ranked Lists for Information Retrieval.
How Do We Move: Modeling Human Movement with System Dynamics.
Learning to Recommend from Sparse Data via Generative User Feedback.
Reinforcement Learning with a Disentangled Universal Value Function for Item Recommendation.
Coupling Macro-Sector-Micro Financial Indicators for Learning Stock Representations with Less Uncertainty.
Reinforced Imitative Graph Representation Learning for Mobile User Profiling: An Adversarial Training Perspective.
GSNet: Learning Spatial-Temporal Correlations from Geographical and Semantic Aspects for Traffic Accident Risk Forecasting.
GaussianPath: A Bayesian Multi-Hop Reasoning Framework for Knowledge Graph Reasoning.
Dynamic Memory based Attention Network for Sequential Recommendation.
Hyperbolic Variational Graph Neural Network for Modeling Dynamic Graphs.
A Hybrid Probabilistic Approach for Table Understanding.
Detecting Beneficial Feature Interactions for Recommender Systems.
Group Testing on a Network.
Knowledge-Driven Distractor Generation for Cloze-Style Multiple Choice Questions.
DocParser: Hierarchical Document Structure Parsing from Renderings.
U-BERT: Pre-training User Representations for Improved Recommendation.
Robust Spatio-Temporal Purchase Prediction via Deep Meta Learning.
Learning Accurate and Interpretable Decision Rule Sets from Neural Networks.
Communicative Message Passing for Inductive Relation Reasoning.
Knowledge-Enhanced Top-K Recommendation in Poincaré Ball.
Learning to Pre-train Graph Neural Networks.
Relative and Absolute Location Embedding for Few-Shot Node Classification on Graph.
Visual Pivoting for (Unsupervised) Entity Alignment.
Noninvasive Self-attention for Side Information Fusion in Sequential Recommendation.
Pre-training Context and Time Aware Location Embeddings from Spatial-Temporal Trajectories for User Next Location Prediction.
HMS: A Hierarchical Solver with Dependency-Enhanced Understanding for Math Word Problem.
FedRec++: Lossless Federated Recommendation with Explicit Feedback.
Cross-Oilfield Reservoir Classification via Multi-Scale Sensor Knowledge Transfer.
GraphMSE: Efficient Meta-path Selection in Semantically Aligned Feature Space for Graph Neural Networks.
Rejection Sampling for Weighted Jaccard Similarity Revisited.
Spatial-Temporal Fusion Graph Neural Networks for Traffic Flow Forecasting.
Hierarchical Negative Binomial Factorization for Recommender Systems on Implicit Feedback.
Disposable Linear Bandits for Online Recommendations.
PREMERE: Meta-Reweighting via Self-Ensembling for Point-of-Interest Recommendation.
Randomized Generation of Adversary-aware Fake Knowledge Graphs to Combat Intellectual Property Theft.
On Estimating Recommendation Evaluation Metrics under Sampling.
LREN: Low-Rank Embedded Network for Sample-Free Hyperspectral Anomaly Detection.
Anomaly Attribution with Likelihood Compensation.
Graph-Enhanced Multi-Task Learning of Multi-Level Transition Dynamics for Session-based Recommendation.
Knowledge-aware Coupled Graph Neural Network for Social Recommendation.
Online Learning in Variable Feature Spaces under Incomplete Supervision.
Complete Closed Time Intervals-Related Patterns Mining.
GAN Ensemble for Anomaly Detection.
Joint Air Quality and Weather Prediction Based on Multi-Adversarial Spatiotemporal Networks.
NeuralAC: Learning Cooperation and Competition Effects for Match Outcome Prediction.
Exploiting Behavioral Consistence for Universal User Representation.
Neural Latent Space Model for Dynamic Networks and Temporal Knowledge Graphs.
Estimating the Number of Induced Subgraphs from Incomplete Data and Neighborhood Queries.
A Hybrid Bandit Framework for Diversified Recommendation.
Graph Neural Network-Based Anomaly Detection in Multivariate Time Series.
PASSLEAF: A Pool-bAsed Semi-Supervised LEArning Framework for Uncertain Knowledge Graph Embedding.
Deep Transfer Tensor Decomposition with Orthogonal Constraint for Recommender Systems.
Towards Faster Deep Collaborative Filtering via Hierarchical Decision Networks.
Leveraging Table Content for Zero-shot Text-to-SQL with Meta-Learning.
A User-Adaptive Layer Selection Framework for Very Deep Sequential Recommender Models.
Revisiting Consistent Hashing with Bounded Loads.
Efficient Optimal Selection for Composited Advertising Creatives with Tree Structure.
Graph Heterogeneous Multi-Relational Recommendation.
Beyond Low-frequency Information in Graph Convolutional Networks.
Extreme k-Center Clustering.
Parameterizing Branch-and-Bound Search Trees to Learn Branching Policies.
Symmetric Component Caching for Model Counting on Combinatorial Instances.
LCollision: Fast Generation of Collision-Free Human Poses using Learned Non-Penetration Constraints.
SAT-based Decision Tree Learning for Large Data Sets.
Turbocharging Treewidth-Bounded Bayesian Network Structure Learning.
Satisfiability and Algorithms for Non-uniform Random k-SAT.
Dependency Stochastic Boolean Satisfiability: A Logical Formalism for NEXPTIME Decision Problems with Uncertainty.
Towards More Practical and Efficient Automatic Dominance Breaking.
Parallel Constraint Acquisition.
The Power of Literal Equivalence in Model Counting.
On Continuous Local BDD-Based Search for Hybrid SAT Solving.
Backdoor Decomposable Monotone Circuits and Propagation Complete Encodings.
Binary Matrix Factorisation via Column Generation.
Smooth Convex Optimization Using Sub-Zeroth-Order Oracles.
A Scalable Two Stage Approach to Computing Optimal Decision Sets.
Integrated Optimization of Bipartite Matching and Its Stochastic Behavior: New Formulation and Approximation Algorithm via Min-cost Flow Optimization.
Scalable Verification of Quantized Neural Networks.
Finding Diverse Trees, Paths, and More.
Certifying Parity Reasoning Efficiently Using Pseudo-Boolean Proofs.
Optimising Automatic Calibration of Electric Muscle Stimulation.
Cutting to the Core of Pseudo-Boolean Optimization: Combining Core-Guided Search with Cutting Planes Reasoning.
Teaching the Old Dog New Tricks: Supervised Learning with Constraints.
Optimal Decision Trees for Nonlinear Metrics.
Disjunctive Temporal Problems under Structural Restrictions.
Solving Infinite-Domain CSPs Using the Patchwork Property.
An Improved Upper Bound for SAT.
A Sharp Leap from Quantified Boolean Formula to Stochastic Boolean Satisfiability Solving.
Necessary and Sufficient Conditions for Avoiding Reopenings in Best First Suboptimal Search with General Bounding Functions.
Combining Reinforcement Learning and Constraint Programming for Combinatorial Optimization.
A SAT-based Resolution of Lam's Problem.
Learning To Scale Mixed-Integer Programs.
Counting Maximal Satisfiable Subsets.
Online Search with Maximum Clearance.
New Length Dependent Algorithm for Maximum Satisfiability Problem.
ASHF-Net: Adaptive Sampling and Hierarchical Folding Network for Robust Point Cloud Completion.
Fooling Thermal Infrared Pedestrian Detectors in Real World Using Small Bulbs.
Simple is not Easy: A Simple Strong Baseline for TextVQA and TextCaps.
Inferring Camouflaged Objects by Texture-Aware Interactive Guidance Network.
Optimizing Information Theory Based Bitwise Bottlenecks for Efficient Mixed-Precision Activation Quantization.
Model Uncertainty Guides Visual Object Tracking.
Deep Semantic Dictionary Learning for Multi-label Image Classification.
Regional Attention with Architecture-Rebuilt 3D Network for RGB-D Gesture Recognition.
CIA-SSD: Confident IoU-Aware Single-Stage Object Detector From Point Cloud.
RESA: Recurrent Feature-Shift Aggregator for Lane Detection.
Exploiting Sample Uncertainty for Domain Adaptive Person Re-Identification.
Robust Multi-Modality Person Re-identification.
Joint Color-irrelevant Consistency Learning and Identity-aware Modality Adaptation for Visible-infrared Cross Modality Person Re-identification.
Robust Lightweight Facial Expression Recognition Network with Label Distribution Training.
ePointDA: An End-to-End Simulation-to-Real Domain Adaptation Framework for LiDAR Point Cloud Segmentation.
Context-Guided Adaptive Network for Efficient Human Pose Estimation.
Distribution Adaptive INT8 Quantization for Training CNNs.
IA-GM: A Deep Bidirectional Learning Method for Graph Matching.
Learning Flexibly Distributional Representation for Low-quality 3D Face Recognition.
Depth Privileged Object Detection in Indoor Scenes via Deformation Hallucination.
Bag of Tricks for Long-Tailed Visual Recognition with Deep Convolutional Neural Networks.
Efficient License Plate Recognition via Holistic Position Attention.
PC-RGNN: Point Cloud Completion and Graph Neural Network for 3D Object Detection.
Weakly Supervised Semantic Segmentation for Large-Scale Point Cloud.
Diverse Knowledge Distillation for End-to-End Person Search.
BoW Pooling: A Plug-and-Play Unit for Feature Aggregation of Point Clouds.
Consensus Graph Representation Learning for Better Grounded Image Captioning.
Point Cloud Semantic Scene Completion from RGB-D Images.
A Novel Visual Interpretability for Deep Neural Networks by Optimizing Activation Maps with Perturbation.
Proactive Privacy-preserving Learning for Retrieval.
Unsupervised Domain Adaptation for Person Re-identification via Heterogeneous Graph Alignment.
Enhancing Audio-Visual Association with Self-Supervised Curriculum Learning.
SIMPLE: SIngle-network with Mimicking and Point Learning for Bottom-up Human Pose Estimation.
Ada-Segment: Automated Multi-loss Adaptation for Panoptic Segmentation.
One for More: Selecting Generalizable Samples for Generalizable ReID Model.
Visual Tracking via Hierarchical Deep Reinforcement Learning.
SPIN: Structure-Preserving Inner Offset Network for Scene Text Recognition.
Universal Adversarial Perturbations Through the Lens of Deep Steganography: Towards a Fourier Perspective.
EMLight: Lighting Estimation via Spherical Distribution Approximation.
Demodalizing Face Recognition with Synthetic Samples.
StrokeGAN: Reducing Mode Collapse in Chinese Font Generation via Stroke Encoding.
Learning Visual Context for Group Activity Recognition.
Simple and Effective Stochastic Neural Networks.
Fast and Compact Bilinear Pooling by Shifted Random Maclaurin.
Structure-Consistent Weakly Supervised Salient Object Detection with Local Saliency Coherence.
CAKES: Channel-wise Automatic KErnel Shrinking for Efficient 3D Networks.
High-Resolution Deep Image Matting.
ERNIE-ViL: Knowledge Enhanced Vision-Language Representations through Scene Graphs.
Multimodal Fusion via Teacher-Student Network for Indoor Action Recognition.
Instance Mining with Class Feature Banks for Weakly Supervised Object Detection.
A Case Study of the Shortcut Effects in Visual Commonsense Reasoning.
One-shot Face Reenactment Using Appearance Adaptive Normalization.
R3Det: Refined Single-Stage Detector with Feature Refinement for Rotating Object.
CPCGAN: A Controllable 3D Point Cloud Generative Adversarial Network with Semantic Label Generating.
Adversarial Robustness through Disentangled Representations.
Object Relation Attention for Image Paragraph Captioning.
Learning to Attack Real-World Models for Person Re-identification via Virtual-Guided Meta-Learning.
Non-Autoregressive Coarse-to-Fine Video Captioning.
Learning Semantic Context from Normal Samples for Unsupervised Anomaly Detection.
Sparse Single Sweep LiDAR Point Cloud Segmentation via Learning Contextual Shape Priors from Scene Completion.
AnchorFace: An Anchor-based Facial Landmark Detector Across Large Poses.
FaceController: Controllable Attribute Editing for Face in the Wild.
GIF Thumbnails: Attract More Clicks to Your Videos.
Searching for Alignment in Face Recognition.
Learning Geometry-Disentangled Representation for Complementary Understanding of 3D Object Point Cloud.
Investigate Indistinguishable Points in Semantic Segmentation of 3D Point Cloud.
Efficient Deep Image Denoising via Class Specific Convolution.
Self-supervised Multi-view Stereo via Effective Co-Segmentation and Data-Augmentation.
Imagine, Reason and Write: Visual Storytelling with Graph Knowledge and Relational Reasoning.
Invariant Teacher and Equivariant Student for Unsupervised 3D Human Pose Estimation.
Locate Globally, Segment Locally: A Progressive Architecture With Knowledge Review Network for Salient Object Detection.
Amodal Segmentation Based on Visible Region Segmentation and Shape Prior.
Boundary Proposal Network for Two-stage Natural Language Video Localization.
Shape-Pose Ambiguity in Learning 3D Reconstruction from Images.
Beating Attackers At Their Own Games: Adversarial Example Detection Using Adversarial Gradient Directions.
Binaural Audio-Visual Localization.
Anticipating Future Relations via Graph Growing for Action Prediction.
MVFNet: Multi-View Fusion Network for Efficient Video Recognition.
Learning Comprehensive Motion Representation for Action Recognition.
Graph-to-Graph: Towards Accurate and Interpretable Online Handwritten Mathematical Expression Recognition.
Precise Yet Efficient Semantic Calibration and Refinement in ConvNets for Real-time Polyp Segmentation from Colonoscopy Videos.
Region-aware Global Context Modeling for Automatic Nerve Segmentation from Ultrasound Images.
Decentralised Learning from Independent Multi-Domain Labels for Person Re-Identification.
Generalising without Forgetting for Lifelong Person Re-Identification.
Stereopagnosia: Fooling Stereo Networks with Adversarial Perturbations.
Holistic Multi-View Building Analysis in the Wild with Projection Pooling.
Semantic Consistency Networks for 3D Object Detection.
C2F-FWN: Coarse-to-Fine Flow Warping Network for Spatial-Temporal Consistent Motion Transfer.
Geodesic-HOF: 3D Reconstruction Without Cutting Corners.
Confidence-aware Non-repetitive Multimodal Transformers for TextCaps.
Deep Multi-Task Learning for Diabetic Retinopathy Grading in Fundus Images.
Teacher Guided Neural Architecture Search for Face Recognition.
Very Important Person Localization in Unconstrained Conditions: A New Benchmark.
Co-mining: Self-Supervised Learning for Sparsely Annotated Object Detection.
Dynamic Position-aware Network for Fine-grained Image Recognition.
PGNet: Real-time Arbitrarily-Shaped Text Spotting with Point Gathering Network.
Unsupervised 3D Learning for Shape Analysis via Multiresolution Instance Discrimination.
Camera-Aware Proxies for Unsupervised Person Re-Identification.
Weakly Supervised Deep Hyperspherical Quantization for Image Retrieval.
Self-Domain Adaptation for Face Anti-Spoofing.
Towards Robust Visual Information Extraction in Real World: New Dataset and Novel Solution.
Temporal Relational Modeling with Self-Supervision for Action Segmentation.
Efficient Object-Level Visual Context Modeling for Multimodal Machine Translation: Masking Irrelevant Objects Helps Grounding.
Task-Independent Knowledge Makes for Transferable Representations for Generalized Zero-Shot Learning.
SCNet: Training Inference Sample Consistency for Instance Segmentation.
Artificial Dummies for Urban Dataset Augmentation.
Adversarial Turing Patterns from Cellular Automata.
Adversarial Training Reduces Information and Improves Transferability.
Gradient Regularized Contrastive Learning for Continual Domain Adaptation.
Structure-aware Person Image Generation with Pose Decomposition and Semantic Correlation.
Object-Centric Image Generation from Layouts.
Domain General Face Forgery Detection by Learning to Weight.
Deep Probabilistic Imaging: Uncertainty Quantification and Multi-modal Solution Characterization for Computational Imaging.
MAMBA: Multi-level Aggregation via Memory Bank for Video Object Detection.
MangaGAN: Unpaired Photo-to-Manga Translation Based on The Methodology of Manga Drawing.
BSN++: Complementary Boundary Regressor with Scale-Balanced Relation Modeling for Temporal Action Proposal Generation.
Unsupervised Model Adaptation for Continual Semantic Segmentation.
Image Captioning with Context-Aware Auxiliary Guidance.
To Choose or to Fuse? Scale Selection for Crowd Counting.
AttaNet: Attention-Augmented Network for Fast and Accurate Scene Parsing.
Robust Knowledge Transfer via Hybrid Forward on the Teacher-Student Model.
Social-DPF: Socially Acceptable Distribution Prediction of Futures.
Progressive Network Grafting for Few-Shot Knowledge Distillation.
Enhanced Regularizers for Attributional Robustness.
Audio-Visual Localization by Synthetic Acoustic Image Generation.
Semantic Grouping Network for Video Captioning.
Efficient Certification of Spatial Robustness.
DPFPS: Dynamic and Progressive Filter Pruning for Compressing Convolutional Neural Networks from Scratch.
AutoLR: Layer-wise Pruning and Auto-tuning of Learning Rates in Fine-tuning of Deep Networks.
REFINE: Prediction Fusion Network for Panoptic Segmentation.
MANGO: A Mask Attention Guided One-Stage Scene Text Spotter.
Learning Modulated Loss for Rotated Object Detection.
KGDet: Keypoint-Guided Fashion Detection.
Dual Adversarial Graph Neural Networks for Multi-label Cross-modal Retrieval.
Explainable Models with Consistent Interpretations.
CHEF: Cross-modal Hierarchical Embeddings for Food Domain Retrieval.
Vid-ODE: Continuous-Time Video Generation with Neural Ordinary Differential Equation.
Learning Disentangled Representation for Fair Facial Attribute Classification via Fairness-aware Information Alignment.
Few-shot Font Generation with Localized Style Representations and Factorization.
TDAF: Top-Down Attention Framework for Vision Tasks.
Embodied Visual Active Learning for Semantic Segmentation.
Terrace-based Food Counting and Segmentation.
Dynamic Anchor Learning for Arbitrary-Oriented Object Detection.
CARPe Posterum: A Convolutional Approach for Real-Time Pedestrian Path Prediction.
Few-Shot Lifelong Learning.
Scene Graph Embeddings Using Relative Similarity Supervision.
Learning to Count via Unbalanced Optimal Transport.
Pyramidal Feature Shrinking for Salient Object Detection.
SMIL: Multimodal Learning with Severely Missing Modality.
HR-Depth: High Resolution Self-Supervised Monocular Depth Estimation.
Dual-level Collaborative Transformer for Image Captioning.
DeepDT: Learning Geometry From Delaunay Triangulation for Surface Reconstruction.
PC-HMR: Pose Calibration for 3D Human Mesh Recovery from 2D Images/Videos.
A Global Occlusion-Aware Approach to Self-Supervised Monocular Visual Odometry.
PointINet: Point Cloud Frame Interpolation Network.
Weakly Supervised Temporal Action Localization Through Learning Explicit Subspaces for Action and Context.
ACSNet: Action-Context Separation Network for Weakly Supervised Temporal Action Localization.
Aggregated Multi-GANs for Controlled 3D Human Motion Prediction.
Delving into Variance Transmission and Normalization: Shift of Average Gradient Makes the Network Collapse.
Hierarchical Information Passing Based Noise-Tolerant Hybrid Learning for Semi-Supervised Human Parsing.
FontRL: Chinese Font Synthesis via Deep Reinforcement Learning.
Subtype-aware Unsupervised Domain Adaptation for Medical Diagnosis.
Translate the Facial Regions You Like Using Self-Adaptive Region Translation.
Learning Hybrid Relationships for Person Re-identification.
Temporal Segmentation of Fine-gained Semantic Action: A Motion-Centered Figure Skating Dataset.
Adaptive Pattern-Parameter Matching for Robust Pedestrian Detection.
Activity Image-to-Video Retrieval by Disentangling Appearance and Motion.
FCFR-Net: Feature Fusion based Coarse-to-Fine Residual Learning for Depth Completion.
Large Motion Video Super-Resolution with Dual Subnet and Multi-Stage Communicated Upsampling.
Toward Realistic Virtual Try-on Through Landmark Guided Shape Matching.
F2Net: Learning to Focus on the Foreground for Unsupervised Video Object Segmentation.
Spatiotemporal Graph Neural Network based Mask Reconstruction for Video Object Segmentation.
SA-BNN: State-Aware Binary Neural Network.
TIME: Text and Image Mutual-Translation Adversarial Networks.
Self-Supervised Sketch-to-Image Synthesis.
Single View Point Cloud Generation via Unified 3D Prototype.
Exploiting Audio-Visual Consistency with Partial Supervision for Spatial Audio Generation.
Augmented Partial Mutual Learning with Frame Masking for Video Captioning.
Query-Memory Re-Aggregation for Weakly-supervised Video Object Segmentation.
Temporal Pyramid Network for Pedestrian Trajectory Prediction with Multi-Supervision.
SD-Pose: Semantic Decomposition for Cross-Domain 6D Object Pose Estimation.
Sequential End-to-end Network for Efficient Person Search.
Deep Unsupervised Image Hashing by Maximizing Bit Entropy.
Inference Fusion with Associative Semantics for Unseen Object Detection.
Group-Wise Semantic Mining for Weakly Supervised Semantic Segmentation.
Learning Omni-Frequency Region-adaptive Representations for Real Image Super-Resolution.
Generalized Zero-Shot Learning via Disentangled Representation.
Joint Semantic-geometric Learning for Polygonal Building Segmentation.
Category Dictionary Guided Unsupervised Domain Adaptation for Object Detection.
Adversarial Pose Regression Network for Pose-Invariant Face Recognitions.
RTS3D: Real-time Stereo 3D Detection from 4D Feature-Consistency Embedding Space for Autonomous Driving.
Exploiting Learnable Joint Groups for Hand Pose Estimation.
Write-a-speaker: Text-based Emotional and Rhythmic Talking-head Generation.
Proposal-Free Video Grounding with Contextual Pyramid Network.
Static-Dynamic Interaction Networks for Offline Signature Verification.
Semi-Supervised Learning for Multi-Task Scene Understanding by Neural Graph Consensus.
Patch-Wise Attention Network for Monocular Depth Estimation.
Learning Monocular Depth in Dynamic Scenes via Instance-Aware Projection Consistency.
Weakly-supervised Temporal Action Localization by Uncertainty Modeling.
Regularizing Attention Networks for Anomaly Detection in Visual Question Answering.
Dynamic to Static Lidar Scan Reconstruction Using Adversarially Trained Auto Encoder.
Multi-level Distance Regularization for Deep Metric Learning.
DASZL: Dynamic Action Signatures for Zero-shot Learning.
Bidirectional RNN-based Few Shot Learning for 3D Medical Image Segmentation.
Cross-Domain Grouping and Alignment for Domain Adaptive Semantic Segmentation.
Structured Co-reference Graph Attention for Video-grounded Dialogue.
End-to-End Differentiable Learning to HDR Image Synthesis for Multi-exposure Images.
Dual Compositional Learning in Interactive Image Retrieval.
Visual Comfort Aware-Reinforcement Learning for Depth Adjustment of Stereoscopic 3D Images.
Discriminative Region Suppression for Weakly-Supervised Semantic Segmentation.
StarNet: towards Weakly Supervised Few-Shot Object Detection.
Spectral Distribution Aware Image Generation.
Deep Low-Contrast Image Enhancement using Structure Tensor Representation.
Asynchronous Teacher Guided Bit-wise Hard Mining for Online Hashing.
What to Select: Pursuing Consistent Motion Segmentation from Multiple Geometric Models.
Training Binary Neural Network without Batch Normalization for Image Super-Resolution.
SSN3D: Self-Separated Network to Align Parts for 3D Convolution in Video Person Re-Identification.
GradingNet: Towards Providing Reliable Supervisions for Weakly Supervised Object Detection by Grading the Box Candidates.
Matching on Sets: Conquer Occluded Person Re-identification Without Alignment.
Frequency Consistent Adaptation for Real World Super Resolution.
Improving Image Captioning by Leveraging Intra- and Inter-layer Global Representation in Transformer Network.
Context-Aware Graph Convolution Network for Target Re-identification.
A Hybrid Attention Mechanism for Weakly-Supervised Temporal Action Localization.
SnapMix: Semantically Proportional Mixing for Augmenting Fine-grained Data.
Initiative Defense against Facial Manipulation.
Text-Guided Graph Neural Networks for Referring 3D Instance Segmentation.
PTN: A Poisson Transfer Network for Semi-supervised Few-shot Learning.
Modeling Deep Learning Based Privacy Attacks on Physical Mail.
Exploiting Relationship for Complex-scene Image Generation.
VIVO: Visual Vocabulary Pre-Training for Novel Object Captioning.
Stratified Rule-Aware Network for Abstract Visual Reasoning.
Hand-Model-Aware Sign Language Recognition.
DropLoss for Long-Tail Instance Segmentation.
Error-Aware Density Isomorphism Reconstruction for Unsupervised Cross-Domain Crowd Counting.
Consistent-Separable Feature Representation for Semantic Segmentation.
Progressive One-shot Human Parsing.
Spherical Image Generation from a Single Image by Considering Scene Symmetry.
Decoupled and Memory-Reinforced Networks: Towards Effective Feature Learning for One-Step Person Search.
Order Regularization on Ordinal Loss for Head Pose, Age and Gaze Estimation.
EfficientDeRain: Learning Pixel-wise Dilation Filtering for High-Efficiency Single-Image Deraining.
Class-Incremental Instance Segmentation via Multi-Teacher Networks.
Interpretable Graph Capsule Networks for Object Recognition.
Proxy Synthesis: Learning with Synthetic Classes for Deep Metric Learning.
SMART Frame Selection for Action Recognition.
Temporal ROI Align for Video Object Recognition.
Analogical Image Translation for Fog Generation.
Boundary-Aware Geometric Encoding for Semantic Segmentation of Point Clouds.
Dynamic Graph Representation Learning for Video Dialog via Multi-Modal Shuffled Transformers.
Semantic-guided Reinforced Region Embedding for Generalized Zero-Shot Learning.
Learning Local Neighboring Structure for Robust 3D Shape Representation.
The Complexity of Object Association in Multiple Object Tracking.
A Systematic Evaluation of Object Detection Networks for Scientific Plots.
Deep Metric Learning with Self-Supervised Ranking.
CompFeat: Comprehensive Feature Aggregation for Video Instance Segmentation.
Rain Streak Removal via Dual Graph Convolutional Network.
Learning Complex 3D Human Self-Contact.
Visual Boundary Knowledge Translation for Foreground Segmentation.
Edge-competing Pathological Liver Vessel Segmentation with Limited Labels.
Memory-Augmented Image Captioning.
Partially Non-Autoregressive Image Captioning.
DecAug: Augmenting HOI Detection via Decomposition.
DIRV: Dense Interaction Region Voting for End-to-End Human-Object Interaction Detection.
How to Save your Annotation Cost for Panoptic Segmentation?
Boosting Image-based Mutual Gaze Detection using Pseudo 3D Gaze.
MIEHDR CNN: Main Image Enhancement based Ghost-Free High Dynamic Range Imaging using Dual-Lens Systems.
Few-Shot Class-Incremental Learning via Relation Knowledge Distillation.
Modeling the Probabilistic Distribution of Unlabeled Data for One-shot Medical Image Segmentation.
Towards Universal Physical Attacks on Single Object Tracking.
Spatio-Temporal Difference Descriptor for Skeleton-Based Action Recognition.
Similarity Reasoning and Filtration for Image-Text Matching.
Arbitrary Video Style Transfer via Multi-Channel Correlation.
Voxel R-CNN: Towards High Performance Voxel-based 3D Object Detection.
RSGNet: Relation based Skeleton Graph Network for Crowded Scenes Pose Estimation.
Split then Refine: Stacked Attention-guided ResUNets for Blind Single Image Visible Watermark Removal.
DeepCollaboration: Collaborative Generative and Discriminative Models for Class Incremental Learning.
DramaQA: Character-Centered Video Story Understanding with Hierarchical QA.
Graph and Temporal Convolutional Networks for 3D Multi-person Pose Estimation in Monocular Videos.
Deep Feature Space Trojan Attack of Neural Networks by Controlled Detoxification.
SSPC-Net: Semi-supervised Semantic 3D Point Cloud Segmentation Network.
Generalizable Representation Learning for Mixture Domain Face Anti-Spoofing.
Cascade Network with Guided Loss and Hybrid Attention for Finding Good Correspondences.
Multi-Scale Spatial Temporal Graph Convolutional Network for Skeleton-Based Action Recognition.
SSD-GAN: Measuring the Realness in the Spatial and Spectral Domains.
A Unified Multi-Scenario Attacking Network for Visual Object Tracking.
Deductive Learning for Weakly-Supervised 3D Human Pose Estimation via Uncalibrated Cameras.
Local Relation Learning for Face Forgery Detection.
Mind-the-Gap! Unsupervised Domain Adaptation for Text-Video Retrieval.
RGB-D Salient Object Detection via 3D Convolutional Neural Networks.
Dual Distribution Alignment Network for Generalizable Person Re-Identification.
RSPNet: Relative Speed Perception for Unsupervised Video Representation Learning.
Ref-NMS: Breaking Proposal Bottlenecks in Two-Stage Referring Expression Grounding.
Spatial-temporal Causal Inference for Partial Image-to-video Adaptation.
Joint Demosaicking and Denoising in the Wild: The Case of Training Under Ground Truth Uncertainty.
Attention-based Multi-Level Fusion Network for Light Field Depth Estimation.
Commonsense Knowledge Aware Concept Selection For Diverse and Informative Visual Storytelling.
CNN Profiler on Polar Coordinate Images for Tropical Cyclone Structure Analysis.
Deep Metric Learning with Graph Consistency.
Understanding Deformable Alignment in Video Super-Resolution.
Semantic MapNet: Building Allocentric Semantic Maps and Representations from Egocentric Views.
YOLObile: Real-Time Object Detection on Mobile Devices via Compression-Compilation Co-Design.
Rethinking Object Detection in Retail Stores.
Appearance-Motion Memory Consistency Network for Video Anomaly Detection.
Context-aware Attentional Pooling (CAP) for Fine-grained Visual Classification.
Dense Events Grounding in Video.
Disentangled Multi-Relational Graph Convolutional Network for Pedestrian Trajectory Prediction.
Motion-blurred Video Interpolation and Extrapolation.
Optical Flow Estimation from a Single Motion-blurred Image.
Deep Event Stereo Leveraged by Event-to-Image Translation.
Localization in the Crowd with Topological Constraints.
Plug-and-Play Domain Adaptation for Cross-Subject EEG-based Emotion Recognition.
Riemannian Embedding Banks for Common Spatial Patterns with EEG-based SPD Neural Networks.
PHASE: PHysically-grounded Abstract Social Events for Machine Social Perception.
Towards a Better Understanding of VR Sickness: Physical Symptom Prediction for VR Contents.
Quantum Cognitively Motivated Decision Fusion for Video Sentiment Analysis.
Interpretable Self-Supervised Facial Micro-Expression Learning to Predict Cognitive State and Neurological Disorders.
Neural Analogical Matching.
Visual Relation Detection using Hybrid Analogical Learning.
Apparently Irrational Choice as Optimal Sequential Decision Making.
Model-Agnostic Fits for Understanding Information Seeking Patterns in Humans.
Probabilistic Programming Bots in Intuitive Physics Game Play.
Many-to-One Distribution Learning and K-Nearest Neighbor Smoothing for Thoracic Disease Identification.
Towards Balanced Defect Prediction with Better Information Propagation.
DEAR: Deep Reinforcement Learning for Online Advertising Impression in Recommender Systems.
Online 3D Bin Packing with Constrained Deep Reinforcement Learning.
A Spatial Regulated Patch-Wise Approach for Cervical Dysplasia Diagnosis.
Window Loss for Bone Fracture Detection and Localization in X-ray Images with Point-based Annotation.
GRASP: Generic Framework for Health Status Representation Learning Based on Incorporating Knowledge from Similar Patients.
Bigram and Unigram Based Text Attack via Adaptive Monotonic Heuristic Search.
Minimizing Labeling Cost for Nuclei Instance Segmentation and Classification with Cross-domain Images and Weak Labels.
Towards Efficient Selection of Activity Trajectories based on Diversity and Coverage.
Deep Partial Rank Aggregation for Personalized Attributes.
Hierarchically and Cooperatively Learning Traffic Signal Control.
Automated Symbolic Law Discovery: A Computer Vision Approach.
Dynamic Gaussian Mixture based Deep Generative Model For Robust Forecasting on Sparse Multivariate Time Series.
DeepTrader: A Deep Reinforcement Learning Approach for Risk-Return Balanced Portfolio Management with Market Conditions Embedding.
Alternative Baselines for Low-Shot 3D Medical Image Segmentation - An Atlas Perspective.
Commission Fee is not Enough: A Hierarchical Reinforced Framework for Portfolio Management.
PSSM-Distil: Protein Secondary Structure Prediction (PSSP) on Low-Quality PSSM by Knowledge Distillation with Contrastive Learning.
Sketch Generation with Drawing Process Guided by Vector Flow and Grayscale.
DeepWriteSYN: On-Line Handwriting Synthesis via Deep Short-Term Representations.
A Hierarchical Approach to Multi-Event Survival Analysis.
Fully Exploiting Cascade Graphs for Real-time Forwarding Prediction.
Traffic Shaping in E-Commercial Search Engine: Multi-Objective Online Welfare Maximization.
Oral-3D: Reconstructing the 3D Structure of Oral Cavity from Panoramic X-ray.
Embracing Domain Differences in Fake News: Cross-domain Fake News Detection using Multi-modal Data.
The LOB Recreation Model: Predicting the Limit Order Book from TAQ History Using an Ordinary Differential Equation Recurrent Neural Network.
Physics-Informed Deep Learning for Traffic State Estimation: A Hybrid Paradigm Informed By Second-Order Traffic Models.
GTA: Graph Truncated Attention for Retrosynthesis.
Integrating Static and Dynamic Data for Improved Prediction of Cognitive Declines Using Augmented Genotype-Phenotype Representations.
StatEcoNet: Statistical Ecology Neural Networks for Species Distribution Modeling.
Content Masked Loss: Human-Like Brush Stroke Planning in a Reinforcement Learning Painting Agent.
Stock Selection via Spatiotemporal Hypergraph Attention Network: A Learning to Rank Approach.
CardioGAN: Attentive Generative Adversarial Network with Dual Discriminators for Synthesis of ECG from PPG.
DeepPseudo: Pseudo Value Based Deep Learning Models for Competing Risk Analysis.
Research Reproducibility as a Survival Analysis.
Queue-Learning: A Reinforcement Learning Approach for Providing Quality of Service.
RareBERT: Transformer Architecture for Rare Disease Patient Identification using Administrative Claims.
Pragmatic Code Autocomplete.
XraySyn: Realistic View Synthesis From a Single Radiograph Through CT Priors.
Deep Just-In-Time Inconsistency Detection Between Comments and Source Code.
Bringing UMAP Closer to the Speed of Light with GPU Acceleration.
Symbolic Music Generation with Transformer-GANs.
Low-Rank Registration Based Manifolds for Convection-Dominated PDEs.
Capturing Uncertainty in Unsupervised GPS Trajectory Segmentation Using Bayesian Deep Learning.
Programmatic Strategies for Real-Time Strategy Games.
PANTHER: Pathway Augmented Nonnegative Tensor Factorization for HighER-order Feature Learning.
RNA Secondary Structure Representation Network for RNA-proteins Binding Prediction.
Deep Style Transfer for Line Drawings.
Relational Classification of Biological Cells in Microscopy Images.
In-game Residential Home Planning via Visual Context-aware Global Relation Learning.
Asynchronous Stochastic Gradient Descent for Extreme-Scale Recommender Systems.
Community-Aware Multi-Task Transportation Demand Prediction.
MeInGame: Create a Game Character Face from a Single Portrait.
RevMan: Revenue-aware Multi-task Online Insurance Recommendation.
Traffic Flow Prediction with Vehicle Trajectories.
Two-Stream Convolution Augmented Transformer for Human Activity Recognition.
Deep Conservation: A Latent-Dynamics Model for Exact Satisfaction of Physical Conservation Laws.
Predicting Livelihood Indicators from Community-Generated Street-Level Imagery.
Learning to Stop: Dynamic Simulation Monte-Carlo Tree Search.
Deep Contextual Clinical Prediction with Reverse Distillation.
Estimating Calibrated Individualized Survival Curves with Deep Learning.
Who You Would Like to Share With? A Study of Share Recommendation in Social E-commerce.
Complex Coordinate-Based Meta-Analysis with Probabilistic Programming.
Deep Portfolio Optimization via Distributional Prediction of Residual Factors.
The Causal Learning of Retail Delinquency.
SDGNN: Learning Node Representation for Signed Directed Networks.
Modeling the Compatibility of Stem Tracks to Generate Music Mashups.
Compound Word Transformer: Learning to Compose Full-Song Music over Dynamic Directed Hypergraphs.
Sub-Seasonal Climate Forecasting via Machine Learning: Challenges, Analysis, and Advances.
Automated Lay Language Summarization of Biomedical Scientific Reviews.
Hierarchical Graph Convolution Network for Traffic Forecasting.
Towered Actor Critic For Handling Multiple Action Types In Reinforcement Learning For Drug Discovery.
ECG ODE-GAN: Learning Ordinary Differential Equations of ECG Dynamics via Generative Adversarial Learning.
MIMOSA: Multi-constraint Molecule Sampling for Molecule Optimization.
Dual-Octave Convolution for Accelerated Parallel MR Image Reconstruction.
Universal Trading for Order Execution with Oracle Policy Distillation.
Gene Regulatory Network Inference using 3D Convolutional Neural Network.
When Hashing Met Matching: Efficient Spatio-Temporal Search for Ridesharing.
KAN: Knowledge-aware Attention Network for Fake News Detection.
Graph Neural Network to Dilute Outliers for Refactoring Monolith Application.
Differentially Private Link Prediction with Protected Connections.
Modeling the Momentum Spillover Effect for Stock Prediction via Attribute-Driven Graph Attention Networks.
Diagnose Like A Pathologist: Weakly-Supervised Pathologist-Tree Network for Slide-Level Immunohistochemical Scoring.
A Bottom-Up DAG Structure Extraction Model for Math Word Problems.
TreeCaps: Tree-Based Capsule Networks for Source Code Processing.
Optimal Kidney Exchange with Immunosuppressants.
Efficient Poverty Mapping from High Resolution Remote Sensing Images.
The Undergraduate Games Corpus: A Dataset for Machine Perception of Interactive Media.
