aaai 2020 论文列表
The Thirty-Fourth AAAI Conference on Artificial Intelligence, AAAI 2020, The Thirty-Second Innovative Applications of Artificial Intelligence Conference, IAAI 2020, The Tenth AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2020, New York, NY, USA, February 7-12, 2020.
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Position-Based Social Choice Methods for Intransitive Incomplete Pairwise Vote Sets (Student Abstract).
Combating False Negatives in Adversarial Imitation Learning (Student Abstract).
Generative Adversarial Imitation Learning from Failed Experiences (Student Abstract).
Contention-Aware Mapping and Scheduling Optimization for NoC-Based MPSoCs (Student Abstract).
HARK: Harshness-Aware Sentiment Analysis Framework for Product Review (Student Abstract).
Focusing on Detail: Deep Hashing Based on Multiple Region Details (Student Abstract).
Clearing Kidney Exchanges via Graph Neural Network Guided Tree Search (Student Abstract).
Rception: Wide and Deep Interaction Networks for Machine Reading Comprehension (Student Abstract).
Shoreline: Data-Driven Threshold Estimation of Online Reserves of Cryptocurrency Trading Platforms (Student Abstract).
Literature Mining for Incorporating Inductive Bias in Biomedical Prediction Tasks (Student Abstract).
Cancer Treatment Classification with Electronic Medical Health Records (Student Abstract).
Domain Knowledge-Assisted Automatic Diagnosis of Idiopathic Pulmonary Fibrosis (IPF) Using High Resolution Computed Tomography (HRCT) (Student Abstract).
Interactive Neural Network: Leveraging Part-of-Speech Window for Aspect Term Extraction (Student Abstract).
Deep Ranking for Style-Aware Room Recommendations (Student Abstract).
Session-Level User Satisfaction Prediction for Customer Service Chatbot in E-Commerce (Student Abstract).
I Know Where You Are Coming From: On the Impact of Social Media Sources on AI Model Performance (Student Abstract).
Breakdown Detection in Negotiation Dialogues (Student Abstract).
Multi-Channel Convolutional Neural Networks with Adversarial Training for Few-Shot Relation Classification (Student Abstract).
Multi-Agent/Robot Deep Reinforcement Learning with Macro-Actions (Student Abstract).
A Multi-Task Learning Machine Reading Comprehension Model for Noisy Document (Student Abstract).
Few Sample Learning without Data Storage for Lifelong Stream Mining (Student Abstract).
Supervised Discovery of Unknown Unknowns through Test Sample Mining (Student Abstract).
Neural Dynamics and Gamma Oscillation on a Hybrid Excitatory-Inhibitory Complex Network (Student Abstract).
Topic Enhanced Controllable CVAE for Dialogue Generation (Student Abstract).
HGMAN: Multi-Hop and Multi-Answer Question Answering Based on Heterogeneous Knowledge Graph (Student Abstract).
Combining Fine-Tuning with a Feature-Based Approach for Aspect Extraction on Reviews (Student Abstract).
Optimal Exploration Algorithm of Multi-Agent Reinforcement Learning Methods (Student Abstract).
Learning Sense Representation from Word Representation for Unsupervised Word Sense Disambiguation (Student Abstract).
Action Recognition and State Change Prediction in a Recipe Understanding Task Using a Lightweight Neural Network Model (Student Abstract).
Towards Interpretable Semantic Segmentation via Gradient-Weighted Class Activation Mapping (Student Abstract).
Emergence of Writing Systems through Multi-Agent Cooperation (Student Abstract).
Robust Multi-View Representation Learning (Student Abstract).
Semantics- and Syntax-Related Subvectors in the Skip-Gram Embeddings (Student Abstract).
Improving First-Order Optimization Algorithms (Student Abstract).
Biologically Inspired Sleep Algorithm for Reducing Catastrophic Forgetting in Neural Networks.
Keyphrase Generation for Scientific Articles Using GANs (Student Abstract).
Sampling Random Chordal Graphs by MCMC (Student Abstract).
Structure-Based Drug-Drug Interaction Detection via Expressive Graph Convolutional Networks and Deep Sets (Student Abstract).
Link Prediction between Group Entities in Knowledge Graphs (Student Abstract).
Leakage-Robust Classifier via Mask-Enhanced Training (Student Abstract).
Using Chinese Glyphs for Named Entity Recognition (Student Abstract).
Bayesian Optimisation for Premise Selection in Automated Theorem Proving (Student Abstract).
On the Hierarchical Information in a Single Contextualised Word Representation (Student Abstract).
SpotFake+: A Multimodal Framework for Fake News Detection via Transfer Learning (Student Abstract).
Providing Uncertainty-Based Advice for Deep Reinforcement Learning Agents (Student Abstract).
Fairness Does Not Imply Satisfaction (Student Abstract).
LGML: Logic Guided Machine Learning (Student Abstract).
A Multi-Task Learning Approach to Sarcasm Detection (Student Abstract).
ERLP: Ensembles of Reinforcement Learning Policies (Student Abstract).
KnowBias: Detecting Political Polarity in Long Text Content (Student Abstract).
Distill BERT to Traditional Models in Chinese Machine Reading Comprehension (Student Abstract).
Opening the Black Box: Automatically Characterizing Software for Algorithm Selection (Student Abstract).
Attribute Noise Robust Binary Classification (Student Abstract).
Predicting Students' Attention Level with Interpretable Facial and Head Dynamic Features in an Online Tutoring System (Student Abstract).
Video Person Re-ID: Fantastic Techniques and Where to Find Them (Student Abstract).
Personalized Prediction of Trust Links in Social Networks (Student Abstract).
A Simple Deconvolutional Mechanism for Point Clouds and Sparse Unordered Data (Student Abstract).
How to Predict Seawater Temperature for Sustainable Marine Aquaculture (Student Abstract).
Transformer-Capsule Model for Intent Detection (Student Abstract).
MUSIC COLLAB: An IoT and ML Based Solution for Remote Music Collaboration (Student Abstract).
A QSAT Benchmark Based on Vertex-Folkman Problems (Student Abstract).
An Analytical Workflow for Clustering Forensic Images (Student Abstract).
Random Projections and α-Shape to Support the Kernel Design (Student Abstract).
Meta-Learning on Graph with Curvature-Based Analysis (Student Abstract).
Suicide Risk Assessment via Temporal Psycholinguistic Modeling (Student Abstract).
Gifting in Multi-Agent Reinforcement Learning (Student Abstract).
Towards Consistent Variational Auto-Encoding (Student Abstract).
Bayesian Adversarial Attack on Graph Neural Networks (Student Abstract).
Generating Engaging Promotional Videos for E-commerce Platforms (Student Abstract).
Constrained Self-Supervised Clustering for Discovering New Intents (Student Abstract).
Adabot: Fault-Tolerant Java Decompiler (Student Abstract).
Towards Minimal Supervision BERT-Based Grammar Error Correction (Student Abstract).
Selecting Portfolios Directly Using Recurrent Reinforcement Learning (Student Abstract).
Travel Time Prediction on Un-Monitored Roads: A Spatial Factorization Machine Based Approach (Student Abstract).
Who Are Controlled by The Same User? Multiple Identities Deception Detection via Social Interaction Activity (Student Abstract).
Submodel Decomposition for Solving Limited Memory Influence Diagrams (Student Abstract).
BattleNet: Capturing Advantageous Battlefield in RTS Games (Student Abstract).
Toward Operational Safety Verification of AI-Enabled CPS (Student Abstract).
Task Scoping for Efficient Planning in Open Worlds (Student Abstract).
Learning to Classify the Wrong Answers for Multiple Choice Question Answering (Student Abstract).
New Off-Board Solution for Predicting Vehicles' Intentions in the Highway On-Ramp Using Probabilistic Classifiers (Student Abstract).
Algorithmic Bias in Recidivism Prediction: A Causal Perspective (Student Abstract).
Multidimensional Analysis of Trust in News Articles (Student Abstract).
A Critique of the Smooth Inverse Frequency Sentence Embeddings (Student Abstract).
Exploring the Benefits of Depth Information in Object Pixel Masking (Student Abstract).
Determining the Possibility of Transfer Learning in Deep Reinforcement Learning Using Grad-CAM (Student Abstract).
Leveraging BERT with Mixup for Sentence Classification (Student Abstract).
Re-Thinking LiDAR-Stereo Fusion Frameworks (Student Abstract).
Learning Directional Sentence-Pair Embedding for Natural Language Reasoning (Student Abstract).
Incremental Sense Weight Training for In-Depth Interpretation of Contextualized Word Embeddings (Student Abstract).
Automatic Text-Based Personality Recognition on Monologues and Multiparty Dialogues Using Attentive Networks and Contextual Embeddings (Student Abstract).
Third-Person Imitation Learning via Image Difference and Variational Discriminator Bottleneck (Student Abstract).
A Multi-Task Approach to Open Domain Suggestion Mining (Student Abstract).
Self-Supervised, Semi-Supervised, Multi-Context Learning for the Combined Classification and Segmentation of Medical Images (Student Abstract).
Streaming Batch Gradient Tracking for Neural Network Training (Student Abstract).
Multi-View Deep Attention Network for Reinforcement Learning (Student Abstract).
Inception LSTM for Next-frame Video Prediction (Student Abstract).
A Bias Trick for Centered Robust Principal Component Analysis (Student Abstract).
Action Graphs for Goal Recognition Problems with Inaccurate Initial States (Student Abstract).
Trimodal Attention Module for Multimodal Sentiment Analysis (Student Abstract).
Hypergraph Convolutional Network for Multi-Hop Knowledge Base Question Answering (Student Abstract).
Modeling Involuntary Dynamic Behaviors to Support Intelligent Tutoring (Student Abstract).
ESAS: Towards Practical and Explainable Short Answer Scoring (Student Abstract).
An Automatic Shoplifting Detection from Surveillance Videos (Student Abstract).
Does Speech Enhancement of Publicly Available Data Help Build Robust Speech Recognition Systems? (Student Abstract).
VECA: A Method for Detecting Overfitting in Neural Networks (Student Abstract).
I Am Guessing You Can't Recognize This: Generating Adversarial Images for Object Detection Using Spatial Commonsense (Student Abstract).
Predicting Opioid Overdose Crude Rates with Text-Based Twitter Features (Student Abstract).
Exploring Abstract Concepts for Image Privacy Prediction in Social Networks (Student Abstract).
Search Tree Pruning for Progressive Neural Architecture Search (Student Abstract).
American Sign Language Recognition Using an FMCW Wireless Sensor (Student Abstract).
Multi-Agent Pattern Formation with Deep Reinforcement Learning (Student Abstract).
Hierarchical Average Reward Policy Gradient Algorithms (Student Abstract).
Efficient Spatial-Temporal Rebalancing of Shareable Bikes (Student Abstract).
When Low Resource NLP Meets Unsupervised Language Model: Meta-Pretraining then Meta-Learning for Few-Shot Text Classification (Student Abstract).
Learning to Model Opponent Learning (Student Abstract).
RPM-Oriented Query Rewriting Framework for E-commerce Keyword-Based Sponsored Search (Student Abstract).
Optimizing the Feature Selection Process for Better Accuracy in Datasets with a Large Number of Features (Student Abstract).
CORAL-DMOEA: Correlation Alignment-Based Information Transfer for Dynamic Multi-Objective Optimization (Student Abstract).
SATNet: Symmetric Adversarial Transfer Network Based on Two-Level Alignment Strategy towards Cross-Domain Sentiment Classification (Student Abstract).
Iterative Learning for Reliable Underwater Link Adaptation (Student Abstract).
Towards an Integrative Educational Recommender for Lifelong Learners (Student Abstract).
Improving Semantic Parsing Using Statistical Word Sense Disambiguation (Student Abstract).
Complex Emotional Intelligence Learning Using Deep Neural Networks (Student Abstract).
Analysis of Parliamentary Debate Transcripts Using Community-Based Graphical Approaches (Student Abstract).
Entity Type Enhanced Neural Model for Distantly Supervised Relation Extraction (Student Abstract).
An Iterative Approach for Identifying Complaint Based Tweets in Social Media Platforms (Student Abstract).
LatRec: Recognizing Goals in Latent Space (Student Abstract).
Sample Complexity Bounds for RNNs with Application to Combinatorial Graph Problems (Student Abstract).
Developing a Machine Learning Tool for Dynamic Cancer Treatment Strategies.
Efficient Predictive Uncertainty Estimators for Deep Probabilistic Models.
Explainability in Autonomous Pedagogical Agents.
Modeling Dynamic Behaviors within Population.
A Reinforcement Learning Approach to Strategic Belief Revelation with Social Influence.
Hybrid Approaches to Fine-Grained Emotion Detection in Social Media Data.
Quantum Probabilistic Models Using Feynman Diagram Rules for Better Understanding the Information Diffusion Dynamics in Online Social Networks.
Abstract Constraints for Safe and Robust Robot Learning from Demonstration.
Optimal Auction Based Automated Negotiation in Realistic Decentralised Market Environments.
Explainable Agency in Reinforcement Learning Agents.
Coalitional Strategic Behaviour in Collective Decision Making.
Partial Correlation-Based Attention for Multivariate Time Series Forecasting.
Abstract Rule Based Pattern Learning with Neural Networks.
Interpreting Multimodal Machine Learning Models Trained for Emotion Recognition to Address Robustness and Privacy Concerns.
Understanding Generalization in Neural Networks for Robustness against Adversarial Vulnerabilities.
Towards Adversarially Robust Knowledge Graph Embeddings.
Modelling a Conversational Agent with Complex Emotional Intelligence.
Ranking and Rating Rankings and Ratings.
Results on a Super Strong Exponential Time Hypothesis.
Abstraction and Refinement in Games with Dynamic Weighted Terrain.
Energy and Policy Considerations for Modern Deep Learning Research.
The St. Petersburg Paradox: A Fresh Algorithmic Perspective.
Constraint Programming for an Efficient and Flexible Block Modeling Solver.
A Commentary on the Unsupervised Learning of Disentangled Representations.
Identifiability from a Combination of Observations and Experiments.
Designing Evaluation Rules That Are Robust to Strategic Behavior.
Reasoning about Political Bias in Content Moderation.
Explaining Image Classifiers Generating Exemplars and Counter-Exemplars from Latent Representations.
Algorithm-in-the-Loop Decision Making.
Restraining Bolts for Reinforcement Learning Agents.
Learning Higher-Order Programs through Predicate Invention.
Interactive Scene Generation via Scene Graphs with Attributes.
Combining Machine Learning Models Using combo Library.
Automatic Car Damage Assessment System: Reading and Understanding Videos as Professional Insurance Inspectors.
PresentationTrainer: Oral Presentation Support System for Impression-Related Feedback.
DRAGON-V: Detection and Recognition of Airplane Goals with Navigational Visualization.
Data-Driven Ranking and Visualization of Products by Competitiveness.
DICR: AI Assisted, Adaptive Platform for Contract Review.
Cognitive Compliance: Assessing Regulatory Risk in Financial Advice Documents.
PARTNER: Human-in-the-Loop Entity Name Understanding with Deep Learning.
Exploratory Navigation and Selective Reading.
LearnIt: On-Demand Rapid Customization for Event-Event Relation Extraction.
PulseSatellite: A Tool Using Human-AI Feedback Loops for Satellite Image Analysis in Humanitarian Contexts.
Deep Poetry: A Chinese Classical Poetry Generation System.
Plan2Dance: Planning Based Choreographing from Music.
CAiRE: An End-to-End Empathetic Chatbot.
GENO - Optimization for Classical Machine Learning Made Fast and Easy.
Diana's World: A Situated Multimodal Interactive Agent.
'Watch the Flu': A Tweet Monitoring Tool for Epidemic Intelligence of Influenza in Australia.
D-Agree: Crowd Discussion Support System Based on Automated Facilitation Agent.
DAMN: Defeasible Reasoning Tool for Multi-Agent Reasoning.
Causal Knowledge Extraction through Large-Scale Text Mining.
Embedding High-Level Knowledge into DQNs to Learn Faster and More Safely.
MatchU: An Interactive Matching Platform.
Doc2Dial: A Framework for Dialogue Composition Grounded in Documents.
MAPF Scenario: Software for Evaluating MAPF Plans on Real Robots.
TraceHub - A Platform to Bridge the Gap between State-of-the-Art Time-Series Analytics and Datasets.
Generalized Arc Consistency Algorithms for Table Constraints: A Summary of Algorithmic Ideas.
On the Robustness of Face Recognition Algorithms Against Attacks and Bias.
Software Testing for Machine Learning.
Let's Learn Their Language? A Case for Planning with Automata-Network Languages from Model Checking.
Developments in Multi-Agent Fair Allocation.
Online Fair Division: A Survey.
Unveiling Hidden Intentions.
Learning on the Job: Online Lifelong and Continual Learning.
Open-World Learning for Radically Autonomous Agents.
AI for Explaining Decisions in Multi-Agent Environments.
AI for Software Quality Assurance Blue Sky Ideas Talk.
Assessing Ethical Thinking about AI.
Collective Information.
Back to the Future for Dialogue Research.
Model AI Assignments 2020.
Coding in the Liberal Arts through Natural Language Processing and Machine Learning.
Minecraft as a Platform for Project-Based Learning in AI.
Using Cloud Tools for Literate Programming to Redesign an AI Course for Non-Traditional College Students.
AISpace2: An Interactive Visualization Tool for Learning and Teaching Artificial Intelligence.
An Experimental Ethics Approach to Robot Ethics Education.
Using AI Techniques in a Serious Game for Socio-Moral Reasoning Development.
Making High-Performance Robots Safe and Easy to Use For an Introduction to Computing.
Teaching Game AI as an Undergraduate Course in Computational Media.
Lessons Learned from Teaching Machine Learning and Natural Language Processing to High School Students.
Multiple Data Augmentation Strategies for Improving Performance on Automatic Short Answer Scoring.
Zhorai: Designing a Conversational Agent for Children to Explore Machine Learning Concepts.
Teaching Undergraduate Artificial Intelligence Classes: An Experiment with an Attendance Requirement.
Teaching Constraint Programming Using Fable-Based Learning.
Geospatial Clustering for Balanced and Proximal Schools.
Semi-Supervised Learning to Perceive Children's Affective States in a Tablet Tutor.
AI Trust in Business Processes: The Need for Process-Aware Explanations.
Using Small Business Banking Data for Explainable Credit Risk Scoring.
Discovery News: A Generic Framework for Financial News Recommendation.
Kanji Workbook: A Writing-Based Intelligent Tutoring System for Learning Proper Japanese Kanji Writing Technique with Instructor-Emulated Assessment.
A Natural Language Processing System for Extracting Evidence of Drug Repurposing from Scientific Publications.
Improving Efficiency of Volunteer-Based Food Rescue Operations.
Draining the Water Hole: Mitigating Social Engineering Attacks with CyberTWEAK.
GRACE: Generating Summary Reports Automatically for Cognitive Assistance in Emergency Response.
EMSContExt: EMS Protocol-Driven Concept Extraction for Cognitive Assistance in Emergency Response.
Automated Utterance Generation.
Chemical and Textual Embeddings for Drug Repurposing.
Iterative Data Programming for Expanding Text Classification Corpora.
Machine-Learning-Based Functional Microcirculation Analysis.
Can Eruptions Be Predicted? Short-Term Prediction of Volcanic Eruptions via Attention-Based Long Short-Term Memory.
A System for Medical Information Extraction and Verification from Unstructured Text.
Calorie Estimation in a Real-World Recipe Service.
A Machine Learning Approach to Identify Houses with High Lead Tap Water Concentrations.
Improving Lives of Indebted Farmers Using Deep Learning: Predicting Agricultural Produce Prices Using Convolutional Neural Networks.
Implicit Skills Extraction Using Document Embedding and Its Use in Job Recommendation.
Improving ECG Classification Using Generative Adversarial Networks.
Online Evaluation of Audiences for Targeted Advertising via Bandit Experiments.
Multi-Task Learning for Diabetic Retinopathy Grading and Lesion Segmentation.
Analog Accelerator for Simulation and Diagnostics.
Automatic Building and Labeling of HD Maps with Deep Learning.
Detecting Suspicious Timber Trades.
Probabilistic Super Resolution for Mineral Spectroscopy.
Did That Lost Ballot Box Cost Me a Seat? Computing Manipulations of STV Elections.
Combining Real-Time Segmentation and Classification of Rehabilitation Exercises with LSTM Networks and Pointwise Boosting.
PIDS: An Intelligent Electric Power Management Platform.
Accelerating Ranking in E-Commerce Search Engines through Contextual Factor Selection.
Clarity: Data-Driven Automatic Assessment of Product Competitiveness.
Question Quality Improvement: Deep Question Understanding for Incident Management in Technical Support Domain.
How Machine Learning is Improving U.S. Navy Customer Support.
Feedback-Based Self-Learning in Large-Scale Conversational AI Agents.
FedVision: An Online Visual Object Detection Platform Powered by Federated Learning.
Embedding Convolution Neural Network-Based Defect Finder for Deployed Vision Inspector in Manufacturing Company Frontec.
Understanding Chat Messages for Sticker Recommendation in Messaging Apps.
Day-Ahead Forecasting of Losses in the Distribution Network.
Automated Conversation Review to Surface Virtual Assistant Misunderstandings: Reducing Cost and Increasing Privacy.
Learning Attentive Pairwise Interaction for Fine-Grained Classification.
iFAN: Image-Instance Full Alignment Networks for Adaptive Object Detection.
Viewpoint-Aware Loss with Angular Regularization for Person Re-Identification.
EEMEFN: Low-Light Image Enhancement via Edge-Enhanced Multi-Exposure Fusion Network.
FASTER Recurrent Networks for Efficient Video Classification.
Towards Omni-Supervised Face Alignment for Large Scale Unlabeled Videos.
Multi-Type Self-Attention Guided Degraded Saliency Detection.
When AWGN-Based Denoiser Meets Real Noises.
Motion-Attentive Transition for Zero-Shot Video Object Segmentation.
Generate, Segment, and Refine: Towards Generic Manipulation Segmentation.
Ladder Loss for Coherent Visual-Semantic Embedding.
Unified Vision-Language Pre-Training for Image Captioning and VQA.
Progressive Bi-C3D Pose Grammar for Human Pose Estimation.
Deep Domain-Adversarial Image Generation for Domain Generalisation.
Discriminative and Robust Online Learning for Siamese Visual Tracking.
Spatial-Temporal Multi-Cue Network for Continuous Sign Language Recognition.
Random Erasing Data Augmentation.
Distance-IoU Loss: Faster and Better Learning for Bounding Box Regression.
MemCap: Memorizing Style Knowledge for Image Captioning.
Multi-Source Distilling Domain Adaptation.
GTNet: Generative Transfer Network for Zero-Shot Object Detection.
Spherical Criteria for Fast and Accurate 360° Object Detection.
JSNet: Joint Instance and Semantic Segmentation of 3D Point Clouds.
Zero-Shot Sketch-Based Image Retrieval via Graph Convolution Network.
Fully Convolutional Network for Consistent Voxel-Wise Correspondence.
Adaptive Unimodal Cost Volume Filtering for Deep Stereo Matching.
Exploiting Motion Information from Unlabeled Videos for Static Image Action Recognition.
When Radiology Report Generation Meets Knowledge Graph.
Find Objects and Focus on Highlights: Mining Object Semantics for Video Highlight Detection via Graph Neural Networks.
FACT: Fused Attention for Clothing Transfer with Generative Adversarial Networks.
Multi-Instance Multi-Label Action Recognition and Localization Based on Spatio-Temporal Pre-Trimming for Untrimmed Videos.
Single Camera Training for Person Re-Identification.
Learning 2D Temporal Adjacent Networks for Moment Localization with Natural Language.
Knowledge Integration Networks for Action Recognition.
AutoRemover: Automatic Object Removal for Autonomous Driving Videos.
Deep Camouflage Images.
3D Crowd Counting via Multi-View Fusion with 3D Gaussian Kernels.
RIS-GAN: Explore Residual and Illumination with Generative Adversarial Networks for Shadow Removal.
Pixel-Aware Deep Function-Mixture Network for Spectral Super-Resolution.
Deep Object Co-Segmentation via Spatial-Semantic Network Modulation.
Model Watermarking for Image Processing Networks.
Rethinking the Image Fusion: A Fast Unified Image Fusion Network based on Proportional Maintenance of Gradient and Intensity.
FDN: Feature Decoupling Network for Head Pose Estimation.
Web-Supervised Network with Softly Update-Drop Training for Fine-Grained Visual Classification.
Shape-Oriented Convolution Neural Network for Point Cloud Analysis.
Reliability Does Matter: An End-to-End Weakly Supervised Semantic Segmentation Approach.
Realistic Face Reenactment via Self-Supervised Disentangling of Identity and Pose.
Human Synthesis and Scene Compositing.
Patchy Image Structure Classification Using Multi-Orientation Region Transform.
Region Normalization for Image Inpainting.
Cascading Convolutional Color Constancy.
Pointwise Rotation-Invariant Network with Adaptive Sampling and 3D Spherical Voxel Convolution.
Cross-Modality Attention with Semantic Graph Embedding for Multi-Label Classification.
Facial Action Unit Intensity Estimation via Semantic Correspondence Learning with Dynamic Graph Convolution.
Joint Super-Resolution and Alignment of Tiny Faces.
Leveraging Multi-View Image Sets for Unsupervised Intrinsic Image Decomposition and Highlight Separation.
Object-Guided Instance Segmentation for Biological Images.
Deep Discriminative CNN with Temporal Ensembling for Ambiguously-Labeled Image Classification.
SM-NAS: Structural-to-Modular Neural Architecture Search for Object Detection.
Context-Transformer: Tackling Object Confusion for Few-Shot Detection.
Release the Power of Online-Training for Robust Visual Tracking.
SOGNet: Scene Overlap Graph Network for Panoptic Segmentation.
Towards Scale-Free Rain Streak Removal via Self-Supervised Fractal Band Learning.
FAN-Face: a Simple Orthogonal Improvement to Deep Face Recognition.
An Adversarial Perturbation Oriented Domain Adaptation Approach for Semantic Segmentation.
Learning to Incorporate Structure Knowledge for Image Inpainting.
Asymmetric Co-Teaching for Unsupervised Cross-Domain Person Re-Identification.
Mining on Heterogeneous Manifolds for Zero-Shot Cross-Modal Image Retrieval.
Gated Convolutional Networks with Hybrid Connectivity for Image Classification.
FAS-Net: Construct Effective Features Adaptively for Multi-Scale Object Detection.
Shape-Aware Organ Segmentation by Predicting Signed Distance Maps.
ZoomNet: Part-Aware Adaptive Zooming Neural Network for 3D Object Detection.
SiamFC++: Towards Robust and Accurate Visual Tracking with Target Estimation Guidelines.
CF-LSTM: Cascaded Feature-Based Long Short-Term Networks for Predicting Pedestrian Trajectory.
GDFace: Gated Deformation for Multi-View Face Image Synthesis.
A Proposal-Based Approach for Activity Image-to-Video Retrieval.
Planar Prior Assisted PatchMatch Multi-View Stereo.
Learning Inverse Depth Regression for Multi-View Stereo with Correlation Cost Volume.
Geometry Sharing Network for 3D Point Cloud Classification and Segmentation.
Universal-RCNN: Universal Object Detector via Transferable Graph R-CNN.
FusionDN: A Unified Densely Connected Network for Image Fusion.
Facial Attribute Capsules for Noise Face Super Resolution.
Video Face Super-Resolution with Motion-Adaptive Feedback Cell.
PI-RCNN: An Efficient Multi-Sensor 3D Object Detector with Point-Based Attentive Cont-Conv Fusion Module.
Segmenting Medical MRI via Recurrent Decoding Cell.
Motion-Based Generator Model: Unsupervised Disentanglement of Appearance, Trackable and Intrackable Motions in Dynamic Patterns.
Adversarial Learning of Privacy-Preserving and Task-Oriented Representations.
Convolutional Hierarchical Attention Network for Query-Focused Video Summarization.
Recognizing Instagram Filtered Images with Feature De-Stylization.
SalSAC: A Video Saliency Prediction Model with Shuffled Attentions and Correlation-Based ConvLSTM.
Patch Proposal Network for Fast Semantic Segmentation of High-Resolution Images.
Distraction-Aware Feature Learning for Human Attribute Recognition via Coarse-to-Fine Attention Mechanism.
Tree-Structured Policy Based Progressive Reinforcement Learning for Temporally Language Grounding in Video.
3D Human Pose Estimation via Explicit Compositional Depth Maps.
CircleNet for Hip Landmark Detection.
Tracklet Self-Supervised Learning for Unsupervised Person Re-Identification.
Online Hashing with Efficient Updating of Binary Codes.
Efficient Querying from Weighted Binary Codes.
Heuristic Black-Box Adversarial Attacks on Video Recognition Models.
3D Single-Person Concurrent Activity Detection Using Stacked Relation Network.
F³Net: Fusion, Feedback and Focus for Salient Object Detection.
Adaptive Cross-Modal Embeddings for Image-Text Alignment.
EFANet: Exchangeable Feature Alignment Network for Arbitrary Style Transfer.
Localize, Assemble, and Predicate: Contextual Object Proposal Embedding for Visual Relation Detection.
Graph-Propagation Based Correlation Learning for Weakly Supervised Fine-Grained Image Classification.
Learning Diverse Stochastic Human-Action Generators by Learning Smooth Latent Transitions.
Pruning from Scratch.
Multi-Label Classification with Label Graph Superimposing.
Task-Aware Monocular Depth Estimation for 3D Object Detection.
Symbiotic Attention with Privileged Information for Egocentric Action Recognition.
Mis-Classified Vector Guided Softmax Loss for Face Recognition.
Consistent Video Style Transfer via Compound Regularization.
One-Shot Learning for Long-Tail Visual Relation Detection.
Decoupled Attention Network for Text Recognition.
RDSNet: A New Deep Architecture forReciprocal Object Detection and Instance Segmentation.
Multi-Speaker Video Dialog with Frame-Level Temporal Localization.
Sparsity-Inducing Binarized Neural Networks.
POST: POlicy-Based Switch Tracking.
Show, Recall, and Tell: Image Captioning with Recall Mechanism.
Temporally Grounding Language Queries in Videos by Contextual Boundary-Aware Prediction.
All You Need Is Boundary: Toward Arbitrary-Shaped Text Spotting.
Context Modulated Dynamic Networks for Actor and Action Video Segmentation with Language Queries.
Cross-Modality Paired-Images Generation for RGB-Infrared Person Re-Identification.
Region-Based Global Reasoning Networks.
Progressive Feature Polishing Network for Salient Object Detection.
TextScanner: Reading Characters in Order for Robust Scene Text Recognition.
Optical Flow in Deep Visual Tracking.
Image Cropping with Composition and Saliency Aware Aesthetic Score Map.
Attention-Based View Selection Networks for Light-Field Disparity Estimation.
Differentiable Meta-Learning Model for Few-Shot Semantic Segmentation.
End-to-End Thorough Body Perception for Person Search.
V-PROM: A Benchmark for Visual Reasoning Using Visual Progressive Matrices.
R²MRF: Defocus Blur Detection via Recurrently Refining Multi-Scale Residual Features.
Relation-Aware Pedestrian Attribute Recognition with Graph Convolutional Networks.
Fine-Grained Recognition: Accounting for Subtle Differences between Similar Classes.
An Efficient Framework for Dense Video Captioning.
Stereoscopic Image Super-Resolution with Stereo Consistent Feature.
Multi-Spectral Salient Object Detection by Adversarial Domain Adaptation.
KPNet: Towards Minimal Face Detector.
Efficient Residual Dense Block Search for Image Super-Resolution.
Identifying Model Weakness with Adversarial Examiner.
Optimal Feature Transport for Cross-View Image Geo-Localization.
Multimodal Interaction-Aware Trajectory Prediction in Crowded Space.
Regularized Fine-Grained Meta Face Anti-Spoofing.
Temporal Interlacing Network.
Hidden Trigger Backdoor Attacks.
Conquering the CNN Over-Parameterization Dilemma: A Volterra Filtering Approach for Action Recognition.
Dynamic Graph Representation for Occlusion Handling in Biometrics.
Improved Visual-Semantic Alignment for Zero-Shot Object Detection.
DGCN: Dynamic Graph Convolutional Network for Efficient Multi-Person Pose Estimation.
Learning Meta Model for Zero- and Few-Shot Face Anti-Spoofing.
FFA-Net: Feature Fusion Attention Network for Single Image Dehazing.
Text Perceptron: Towards End-to-End Arbitrary-Shaped Text Spotting.
Visualizing Deep Networks by Optimizing with Integrated Gradients.
Region-Adaptive Dense Network for Efficient Motion Deblurring.
Differentiable Grammars for Videos.
Exploit and Replace: An Asymmetrical Two-Stream Architecture for Versatile Light Field Saliency Detection.
LCD: Learned Cross-Domain Descriptors for 2D-3D Matching.
Explanation vs Attention: A Two-Player Game to Obtain Attention for VQA.
Relation Network for Person Re-Identification.
Visual Dialogue State Tracking for Question Generation.
Further Understanding Videos through Adverbs: A New Video Task.
Adversarial Cross-Domain Action Recognition with Co-Attention.
Image Formation Model Guided Deep Image Super-Resolution.
Crowd Counting with Decomposed Uncertainty.
Spatial-Temporal Gaussian Scale Mixture Modeling for Foreground Estimation.
Pyramid Attention Aggregation Network for Semantic Segmentation of Surgical Instruments.
Learning to Follow Directions in Street View.
Shallow Feature Based Dense Attention Network for Crowd Counting.
High-Order Residual Network for Light Field Super-Resolution.
Domain Generalization Using a Mixture of Multiple Latent Domains.
Fine-Grained Fashion Similarity Learning by Attribute-Specific Embedding Network.
A Variational Autoencoder with Deep Embedding Model for Generalized Zero-Shot Learning.
An Integrated Enhancement Solution for 24-Hour Colorful Imaging.
Learning Saliency-Free Model with Generic Features for Weakly-Supervised Semantic Segmentation.
Context-Aware Zero-Shot Recognition.
Video Cloze Procedure for Self-Supervised Spatio-Temporal Learning.
Hybrid Graph Neural Networks for Crowd Counting.
Training-Time-Friendly Network for Real-Time Object Detection.
TANet: Robust 3D Object Detection from Point Clouds with Triple Attention.
TEINet: Towards an Efficient Architecture for Video Recognition.
Separate in Latent Space: Unsupervised Single Image Layer Separation.
CBNet: A Novel Composite Backbone Network Architecture for Object Detection.
Learning Cross-Modal Context Graph for Visual Grounding.
A New Dataset and Boundary-Attention Semantic Segmentation for Face Parsing.
Importance-Aware Semantic Segmentation in Self-Driving with Discrete Wasserstein Training.
A Generalized Framework for Edge-Preserving and Structure-Preserving Image Smoothing.
Progressive Boundary Refinement Network for Temporal Action Detection.
Multi-Task Driven Feature Models for Thermal Infrared Tracking.
Morphing and Sampling Network for Dense Point Cloud Completion.
Interactive Dual Generative Adversarial Networks for Image Captioning.
Learned Video Compression via Joint Spatial-Temporal Correlation Exploration.
Federated Learning for Vision-and-Language Grounding Problems.
HAL: Improved Text-Image Matching by Mitigating Visual Semantic Hubs.
Filtration and Distillation: Enhancing Region Attention for Fine-Grained Visual Categorization.
Zero-Shot Learning from Adversarial Feature Residual to Compact Visual Feature.
Weakly-Supervised Video Moment Retrieval via Semantic Completion Network.
Self-Attention ConvLSTM for Spatiotemporal Prediction.
Learning to Deblur Face Images via Sketch Synthesis.
Learning Cross-Aligned Latent Embeddings for Zero-Shot Cross-Modal Retrieval.
Learning to Transfer: Unsupervised Domain Translation via Meta-Learning.
Fast Learning of Temporal Action Proposal via Dense Boundary Generator.
Multimodal Structure-Consistent Image-to-Image Translation.
Object Instance Mining for Weakly Supervised Object Detection.
Real-Time Scene Text Detection with Differentiable Binarization.
Finding Action Tubes with a Sparse-to-Dense Framework.
Learning Transferable Adversarial Examples via Ghost Networks.
Natural Image Matting via Guided Contextual Attention.
Geometry-Driven Self-Supervised Method for 3D Human Pose Estimation.
Relation-Guided Spatial Attention and Temporal Refinement for Video-Based Person Re-Identification.
ScaleNet - Improve CNNs through Recursively Rescaling Objects.
Gated Fully Fusion for Semantic Segmentation.
OVL: One-View Learning for Human Retrieval.
Attention-Based Multi-Modal Fusion Network for Semantic Scene Completion.
Appearance and Motion Enhancement for Video-Based Person Re-Identification.
Domain Conditioned Adaptation Network.
Age Progression and Regression with Spatial Attention Modules.
Hierarchical Knowledge Squeezed Adversarial Network Compression.
Learning Part Generation and Assembly for Structure-Aware Shape Synthesis.
Simple Pose: Rethinking and Improving a Bottom-up Approach for Multi-Person Pose Estimation.
Multi-Spectral Vehicle Re-Identification: A Challenge.
Unicoder-VL: A Universal Encoder for Vision and Language by Cross-Modal Pre-Training.
Multi-Question Learning for Visual Question Answering.
Background Suppression Network for Weakly-Supervised Temporal Action Localization.
Kinematic-Structure-Preserved Representation for Unsupervised 3D Human Pose Estimation.
Adversary for Social Good: Protecting Familial Privacy through Joint Adversarial Attacks.
Unpaired Image Enhancement Featuring Reinforcement-Learning-Controlled Image Editing Software.
JSI-GAN: GAN-Based Joint Super-Resolution and Inverse Tone-Mapping with Pixel-Wise Task-Specific Filters for UHD HDR Video.
FISR: Deep Joint Frame Interpolation and Super-Resolution with a Multi-Scale Temporal Loss.
Spiking-YOLO: Spiking Neural Network for Energy-Efficient Object Detection.
REST: Performance Improvement of a Black Box Model via RL-Based Spatial Transformation.
MULE: Multimodal Universal Language Embedding.
Tell Me What They're Holding: Weakly-Supervised Object Detection with Transferable Knowledge from Human-Object Interaction.
Deep Generative Probabilistic Graph Neural Networks for Scene Graph Generation.
Group-Wise Dynamic Dropout Based on Latent Semantic Variations.
Synthetic Depth Transfer for Monocular 3D Object Pose Estimation in the Wild.
Hide-and-Tell: Learning to Bridge Photo Streams for Visual Storytelling.
Real-Time Object Tracking via Meta-Learning: Efficient Model Adaptation and One-Shot Channel Pruning.
Associative Variational Auto-Encoder with Distributed Latent Spaces and Associators.
Pose-Guided Multi-Granularity Attention Network for Text-Based Person Search.
Overcoming Language Priors in VQA via Decomposed Linguistic Representations.
Semantics-Aligned Representation Learning for Person Re-Identification.
Uncertainty-Aware Multi-Shot Knowledge Distillation for Image-Based Object Re-Identification.
SSAH: Semi-Supervised Adversarial Deep Hashing with Self-Paced Hard Sample Generation.
EAC-Net: Efficient and Accurate Convolutional Network for Video Recognition.
Learning Light Field Angular Super-Resolution via a Geometry-Aware Network.
Rethinking Temporal Fusion for Video-Based Person Re-Identification on Semantic and Time Aspect.
DualVD: An Adaptive Dual Encoding Model for Deep Visual Understanding in Visual Dialogue.
Recurrent Nested Model for Sequence Generation.
Reasoning with Heterogeneous Graph Alignment for Video Question Answering.
Divide and Conquer: Question-Guided Spatio-Temporal Contextual Attention for Video Question Answering.
ElixirNet: Relation-Aware Network Architecture Adaptation for Medical Lesion Detection.
SGAP-Net: Semantic-Guided Attentive Prototypes Network for Few-Shot Human-Object Interaction Recognition.
Weakly-Supervised Video Re-Localization with Multiscale Attention Model.
Domain Adaptive Attention Learning for Unsupervised Person Re-Identification.
AWR: Adaptive Weighting Regression for 3D Hand Pose Estimation.
Relational Prototypical Network for Weakly Supervised Temporal Action Localization.
Part-Level Graph Convolutional Network for Skeleton-Based Action Recognition.
GlobalTrack: A Simple and Strong Baseline for Long-Term Tracking.
Unsupervised Deep Learning via Affinity Diffusion.
Location-Aware Graph Convolutional Networks for Video Question Answering.
Coarse-to-Fine Hyper-Prior Modeling for Learned Image Compression.
GTC: Guided Training of CTC towards Efficient and Accurate Scene Text Recognition.
3D Shape Completion with Multi-View Consistent Inference.
SPSTracker: Sub-Peak Suppression of Response Map for Robust Object Tracking.
Hierarchical Modes Exploring in Generative Adversarial Networks.
Joint Commonsense and Relation Reasoning for Image and Video Captioning.
RoadTagger: Robust Road Attribute Inference with Graph Neural Networks.
Softmax Dissection: Towards Understanding Intra- and Inter-Class Objective for Embedding Learning.
Grapy-ML: Graph Pyramid Mutual Learning for Cross-Dataset Human Parsing.
Temporal Context Enhanced Feature Aggregation for Video Object Detection.
Tensor FISTA-Net for Real-Time Snapshot Compressive Imaging.
Point2Node: Correlation Learning of Dynamic-Node for Point Cloud Feature Modeling.
Complementary-View Multiple Human Tracking.
Robust Conditional GAN from Uncertainty-Aware Pairwise Comparisons.
SADA: Semantic Adversarial Diagnostic Attacks for Autonomous Applications.
MarioNETte: Few-Shot Face Reenactment Preserving Identity of Unseen Targets.
Channel Pruning Guided by Classification Loss and Feature Importance.
Constructing Multiple Tasks for Augmentation: Improving Neural Image Classification with K-Means Features.
Pyramid Constrained Self-Attention Network for Fast Video Salient Object Detection.
FLNet: Landmark Driven Fetching and Learning Network for Faithful Talking Facial Animation Synthesis.
Symmetrical Synthesis for Deep Metric Learning.
Look One and More: Distilling Hybrid Order Relational Knowledge for Cross-Resolution Image Recognition.
Deep Reinforcement Learning for Active Human Pose Estimation.
KnowIT VQA: Answering Knowledge-Based Questions about Videos.
Channel Interaction Networks for Fine-Grained Image Categorization.
Accurate Temporal Action Proposal Generation with Relation-Aware Pyramid Network.
Ultrafast Video Attention Prediction with Coupled Knowledge Distillation.
Dynamic Sampling Network for Semantic Segmentation.
Adversarial Attack on Deep Product Quantization Network for Image Retrieval.
EHSOD: CAM-Guided End-to-End Hybrid-Supervised Object Detection with Cascade Refinement.
Scale-Wise Convolution for Image Restoration.
CIAN: Cross-Image Affinity Net for Weakly Supervised Semantic Segmentation.
Person Tube Retrieval via Language Description.
SubSpace Capsule Network.
Visual Relationship Detection with Low Rank Non-Negative Tensor Decomposition.
FD-GAN: Generative Adversarial Networks with Fusion-Discriminator for Single Image Dehazing.
Cycle-CNN for Colorization towards Real Monochrome-Color Camera Systems.
Every Frame Counts: Joint Learning of Video Segmentation and Optical Flow.
Zero Shot Learning with the Isoperimetric Loss.
Spatio-Temporal Deformable Convolution for Compressed Video Quality Enhancement.
The Missing Data Encoder: Cross-Channel Image Completion with Hide-and-Seek Adversarial Network.
Towards Ghost-Free Shadow Removal via Dual Hierarchical Aggregation Network and Shadow Matting GAN.
DASOT: A Unified Framework Integrating Data Association and Single Object Tracking for Online Multi-Object Tracking.
Channel Attention Is All You Need for Video Frame Interpolation.
Visual Domain Adaptation by Consensus-Based Transfer to Intermediate Domain.
Relational Learning for Joint Head and Human Detection.
PedHunter: Occlusion Robust Pedestrian Detector in Crowded Scenes.
3D Human Pose Estimation Using Spatio-Temporal Networks with Explicit Occlusion Training.
A Coarse-to-Fine Adaptive Network for Appearance-Based Gaze Estimation.
CSPN++: Learning Context and Resource Aware Convolutional Spatial Propagation Networks for Depth Completion.
Video Frame Interpolation via Deformable Separable Convolution.
Global Context-Aware Progressive Aggregation Network for Salient Object Detection.
Frame-Guided Region-Aligned Representation for Video Person Re-Identification.
Expressing Objects Just Like Words: Recurrent Visual Embedding for Image-Text Matching.
Knowledge Graph Transfer Network for Few-Shot Recognition.
Structure-Aware Feature Fusion for Unsupervised Domain Adaptation.
Diversity Transfer Network for Few-Shot Learning.
Rethinking the Bottom-Up Framework for Query-Based Video Localization.
Zero-Shot Ingredient Recognition by Multi-Relational Graph Convolutional Network.
End-to-End Learning of Object Motion Estimation from Retinal Events for Event-Based Object Tracking.
Binarized Neural Architecture Search.
Hierarchical Online Instance Matching for Person Search.
Learning Deep Relations to Promote Saliency Detection.
General Partial Label Learning via Dual Bipartite Graph Autoencoder.
Feature Deformation Meta-Networks in Image Captioning of Novel Objects.
Auto-GAN: Self-Supervised Collaborative Learning for Medical Image Synthesis.
Monocular 3D Object Detection with Decoupled Structured Polygon Estimation and Height-Guided Depth Estimation.
Incremental Multi-Domain Learning with Network Latent Tensor Factorization.
Detecting Human-Object Interactions via Functional Generalization.
PsyNet: Self-Supervised Approach to Object Localization Using Point Symmetric Transformation.
Ultrafast Photorealistic Style Transfer via Neural Architecture Search.
Learning End-to-End Scene Flow by Distilling Single Tasks Knowledge.
Visual Tactile Fusion Object Clustering.
Modular Robot Design Synthesis with Deep Reinforcement Learning.
Dempster-Shafer Theoretic Learning of Indirect Speech Act Comprehension Norms.
RoboCoDraw: Robotic Avatar Drawing with GAN-Based Style Transfer and Time-Efficient Path Optimization.
AtLoc: Attention Guided Camera Localization.
Task and Motion Planning Is PSPACE-Complete.
Adversarial Fence Patrolling: Non-Uniform Policies for Asymmetric Environments.
Long-Term Loop Closure Detection through Visual-Spatial Information Preserving Multi-Order Graph Matching.
On the Problem of Covering a 3-D Terrain.
Learning from Interventions Using Hierarchical Policies for Safe Learning.
That and There: Judging the Intent of Pointing Actions with Robotic Arms.
Factorized Inference in Deep Markov Models for Incomplete Multimodal Time Series.
Modeling Probabilistic Commitments for Maintenance Is Inherently Harder than for Achievement.
A Simultaneous Discover-Identify Approach to Causal Inference in Linear Models.
A New Framework for Online Testing of Heterogeneous Treatment Effect.
Recovering Causal Structures from Low-Order Conditional Independencies.
Gradient-Based Optimization for Bayesian Preference Elicitation.
Beyond the Grounding Bottleneck: Datalog Techniques for Inference in Probabilistic Logic Programs.
Off-Policy Evaluation in Partially Observable Environments.
BOWL: Bayesian Optimization for Weight Learning in Probabilistic Soft Logic.
Tandem Inference: An Out-of-Core Streaming Algorithm for Very Large-Scale Relational Inference.
Few-Shot Bayesian Imitation Learning with Logical Program Policies.
Adversarial Disentanglement with Grouped Observations.
Experimental Design for Optimization of Orthogonal Projection Pursuit Models.
Parallel AND/OR Search for Marginal MAP.
Temporal Logics Over Finite Traces with Uncertainty.
General Transportability - Synthesizing Observations and Experiments from Heterogeneous Domains.
Safe Linear Stochastic Bandits.
Error-Correcting and Verifiable Parallel Inference in Graphical Models.
Estimating Causal Effects Using Weighting-Based Estimators.
The Choice Function Framework for Online Policy Improvement.
Probabilistic Reasoning Across the Causal Hierarchy.
Introducing Probabilistic Bézier Curves for N-Step Sequence Prediction.
Causal Discovery from Multiple Data Sets with Non-Identical Variable Sets.
A MaxSAT-Based Framework for Group Testing.
An Efficient Algorithm for Counting Markov Equivalent DAGs.
Low-Variance Black-Box Gradient Estimates for the Plackett-Luce Distribution.
Causal Transfer for Imitation Learning and Decision Making under Sensor-Shift.
Deception through Half-Truths.
Reliable and Efficient Anytime Skeleton Learning.
A Calculus for Stochastic Interventions: Causal Effect Identification and Surrogate Experiments.
Regret Minimisation in Multi-Armed Bandits Using Bounded Arm Memory.
Learning Fair Naive Bayes Classifiers by Discovering and Eliminating Discrimination Patterns.
Scalable Methods for Computing State Similarity in Deterministic Markov Decision Processes.
Point-Based Methods for Model Checking in Partially Observable Markov Decision Processes.
Exchangeable Generative Models with Flow Scans.
Uncertainty-Aware Search Framework for Multi-Objective Bayesian Optimization.
Multi-Fidelity Multi-Objective Bayesian Optimization: An Output Space Entropy Search Approach.
Deep Bayesian Nonparametric Learning of Rules and Plans from Demonstrations with a Learned Automaton Prior.
Computing Superior Counter-Examples for Conformant Planning.
Refining HTN Methods via Task Insertion with Preferences.
NeoNav: Improving the Generalization of Visual Navigation via Generating Next Expected Observations.
Planning with Abstract Learned Models While Learning Transferable Subtasks.
Neural Architecture Search Using Deep Neural Networks and Monte Carlo Tree Search.
Temporal Planning with Intermediate Conditions and Effects.
Symbolic Top-k Planning.
Active Goal Recognition.
Generalized Planning with Positive and Negative Examples.
Automated Synthesis of Social Laws in STRIPS.
Semantic Attachments for HTN Planning.
Idle Time Optimization for Target Assignment and Path Finding in Sortation Centers.
Monte Carlo Tree Search in Continuous Spaces Using Voronoi Optimistic Optimization with Regret Bounds.
Information Shaping for Enhanced Goal Recognition of Partially-Informed Agents.
Top-Quality Planning: Finding Practically Useful Sets of Best Plans.
Reshaping Diverse Planning.
HDDL: An Extension to PDDL for Expressing Hierarchical Planning Problems.
Novel Is Not Always Better: On the Relation between Novelty and Dominance Pruning.
Solving Sum-of-Costs Multi-Agent Pathfinding with Answer-Set Programming.
Decidability and Complexity of Action-Based Temporal Planning over Dense Time.
Dynamic Control of Probabilistic Simple Temporal Networks.
Time-Inconsistent Planning: Simple Motivation Is Hard to Find.
Lifted Fact-Alternating Mutex Groups and Pruned Grounding of Classical Planning Problems.
Beliefs We Can Believe in: Replacing Assumptions with Data in Real-Time Search.
A New Approach to Plan-Space Explanation: Analyzing Plan-Property Dependencies in Oversubscription Planning.
Optimizing Reachability Sets in Temporal Graphs by Delaying.
Planning and Acting with Non-Deterministic Events: Navigating between Safe States.
Reinforcement Learning of Risk-Constrained Policies in Markov Decision Processes.
POP ≡ POCL, Right? Complexity Results for Partial Order (Causal Link) Makespan Minimization.
On Succinct Groundings of HTN Planning Problems.
Hybrid Compositional Reasoning for Reactive Synthesis from Finite-Horizon Specifications.
LATTE: Latent Type Modeling for Biomedical Entity Linking.
Multimodal Summarization with Guidance of Multimodal Reference.
Who Did They Respond to? Conversation Structure Modeling Using Masked Hierarchical Transformer.
Evaluating Commonsense in Pre-Trained Language Models.
Co-Attention Hierarchical Network: Generating Coherent Long Distractors for Reading Comprehension.
Learning to Compare for Better Training and Evaluation of Open Domain Natural Language Generation Models.
Discourse Level Factors for Sentence Deletion in Text Simplification.
JEC-QA: A Legal-Domain Question Answering Dataset.
A Pre-Training Based Personalized Dialogue Generation Model with Persona-Sparse Data.
Replicate, Walk, and Stop on Syntax: An Effective Neural Network Model for Aspect-Level Sentiment Classification.
Dynamic Reward-Based Dueling Deep Dyna-Q: Robust Policy Learning in Noisy Environments.
Semi-Supervised Text Simplification with Back-Translation and Asymmetric Denoising Autoencoders.
Balancing Quality and Human Involvement: An Effective Approach to Interactive Neural Machine Translation.
Reinforced Curriculum Learning on Pre-Trained Neural Machine Translation Models.
Weakly-Supervised Opinion Summarization by Leveraging External Information.
SG-Net: Syntax-Guided Machine Reading Comprehension.
Semantics-Aware BERT for Language Understanding.
Distilling Knowledge from Well-Informed Soft Labels for Neural Relation Extraction.
Relational Graph Neural Network with Hierarchical Attention for Knowledge Graph Completion.
Task-Oriented Dialog Systems That Consider Multiple Appropriate Responses under the Same Context.
CFGNN: Cross Flow Graph Neural Networks for Question Answering on Complex Tables.
Filling Conversation Ellipsis for Better Social Dialog Understanding.
Learning Conceptual-Contextual Embeddings for Medical Text.
Learning Long- and Short-Term User Literal-Preference with Multimodal Hierarchical Transformer Network for Personalized Image Caption.
DCMN+: Dual Co-Matching Network for Multi-Choice Reading Comprehension.
Structure Learning for Headline Generation.
Exploiting Cross-Lingual Subword Similarities in Low-Resource Document Classification.
Graph LSTM with Context-Gated Mechanism for Spoken Language Understanding.
Multi-Point Semantic Representation for Intent Classification.
Span Model for Open Information Extraction on Accurate Corpus.
Neural Simile Recognition with Cyclic Multitask Learning and Local Attention.
CopyMTL: Copy Mechanism for Joint Extraction of Entities and Relations with Multi-Task Learning.
Improving Context-Aware Neural Machine Translation Using Self-Attentive Sentence Embedding.
Automatic Generation of Headlines for Online Math Questions.
Enhancing Pointer Network for Sentence Ordering with Pairwise Ordering Predictions.
Dialog State Tracking with Reinforced Data Augmentation.
Meta-CoTGAN: A Meta Cooperative Training Paradigm for Improving Adversarial Text Generation.
PHASEN: A Phase-and-Harmonics-Aware Speech Enhancement Network.
MixPoet: Diverse Poetry Generation via Learning Controllable Mixed Latent Space.
Integrating Relation Constraints with Neural Relation Extractors.
A Causal Inference Method for Reducing Gender Bias in Word Embedding Relations.
Causally Denoise Word Embeddings Using Half-Sibling Regression.
Visual Agreement Regularized Training for Multi-Modal Machine Translation.
Be Relevant, Non-Redundant, and Timely: Deep Reinforcement Learning for Real-Time Event Summarization.
End-to-End Bootstrapping Neural Network for Entity Set Expansion.
Generalize Sentence Representation with Self-Inference.
Alternating Language Modeling for Cross-Lingual Pre-Training.
Towards Making the Most of BERT in Neural Machine Translation.
Knowledge and Cross-Pair Pattern Guided Semantic Matching for Question Answering.
Improving Domain-Adapted Sentiment Classification by Deep Adversarial Mutual Learning.
Coordinated Reasoning for Cross-Lingual Knowledge Graph Alignment.
The Value of Paraphrase for Knowledge Base Predicates.
Knowledge Graph Grounded Goal Planning for Open-Domain Conversation Generation.
Hashing Based Answer Selection.
Attentive User-Engaged Adversarial Neural Network for Community Question Answering.
Joint Entity and Relation Extraction with a Hybrid Transformer and Reinforcement Learning Based Model.
Copy or Rewrite: Hybrid Summarization with Hierarchical Reinforcement Learning.
Latent Opinions Transfer Network for Target-Oriented Opinion Words Extraction.
A Dataset for Low-Resource Stylized Sequence-to-Sequence Generation.
Importance-Aware Learning for Neural Headline Editing.
Enhanced Meta-Learning for Cross-Lingual Named Entity Recognition with Minimal Resources.
Acquiring Knowledge from Pre-Trained Model to Neural Machine Translation.
GRET: Global Representation Enhanced Transformer.
Learning Multi-Level Dependencies for Robust Word Recognition.
TextNAS: A Neural Architecture Search Space Tailored for Text Representation.
Go From the General to the Particular: Multi-Domain Translation with Domain Transformation Networks.
Integrating Deep Learning with Logic Fusion for Information Extraction.
Masking Orchestration: Multi-Task Pretraining for Multi-Role Dialogue Representation Learning.
Multi-Level Head-Wise Match and Aggregation in Transformer for Textual Sequence Matching.
Probing Brain Activation Patterns by Dissociating Semantics and Syntax in Sentences.
Multi-Task Self-Supervised Learning for Disfluency Detection.
Storytelling from an Image Stream Using Scene Graphs.
Sentiment Classification in Customer Service Dialogue with Topic-Aware Multi-Task Learning.
Improving Knowledge-Aware Dialogue Generation via Knowledge Base Question Answering.
Bridging the Gap between Pre-Training and Fine-Tuning for End-to-End Speech Translation.
Neural Machine Translation with Byte-Level Subwords.
ReCO: A Large Scale Chinese Reading Comprehension Dataset on Opinion.
Neural Question Generation with Answer Pivot.
Unsupervised Neural Dialect Translation with Commonality and Diversity Modeling.
Target-Aspect-Sentiment Joint Detection for Aspect-Based Sentiment Analysis.
Parsing as Pretraining.
Multi-View Consistency for Relation Extraction via Mutual Information and Structure Prediction.
A Joint Model for Definition Extraction with Syntactic Connection and Semantic Consistency.
A Comparison of Architectures and Pretraining Methods for Contextualized Multilingual Word Embeddings.
An Annotated Corpus of Reference Resolution for Interpreting Common Grounding.
Select, Answer and Explain: Interpretable Multi-Hop Reading Comprehension over Multiple Documents.
Capturing Greater Context for Question Generation.
Sentence Generation for Entity Description with Content-Plan Attention.
Fine-Grained Argument Unit Recognition and Classification.
Image Enhanced Event Detection in News Articles.
Capturing Sentence Relations for Answer Sentence Selection with Multi-Perspective Graph Encoding.
Multi-Label Patent Categorization with Non-Local Attention-Based Graph Convolutional Network.
Boundary Enhanced Neural Span Classification for Nested Named Entity Recognition.
Adapting Language Models for Non-Parallel Author-Stylized Rewriting.
Distributed Representations for Arithmetic Word Problems.
Learning Relationships between Text, Audio, and Video via Deep Canonical Correlation for Multimodal Language Analysis.
TreeGen: A Tree-Based Transformer Architecture for Code Generation.
Generating Diverse Translation by Manipulating Multi-Head Attention.
ERNIE 2.0: A Continual Pre-Training Framework for Language Understanding.
Neural Semantic Parsing in Low-Resource Settings with Back-Translation and Meta-Learning.
SPARQA: Skeleton-Based Semantic Parsing for Complex Questions over Knowledge Bases.
History-Adaption Knowledge Incorporation Mechanism for Multi-Turn Dialogue System.
Learning Sparse Sharing Architectures for Multiple Tasks.
Relation Extraction with Convolutional Network over Learnable Syntax-Transport Graph.
Assessing the Benchmarking Capacity of Machine Reading Comprehension Datasets.
Attractive or Faithful? Popularity-Reinforced Learning for Inspired Headline Generation.
Controlling the Amount of Verbatim Copying in Abstractive Summarization.
Joint Parsing and Generation for Abstractive Summarization.
Alignment-Enhanced Transformer for Constraining NMT with Pre-Specified Translations.
Generating Persona Consistent Dialogues by Exploiting Natural Language Inference.
Modelling Form-Meaning Systematicity with Linguistic and Visual Features.
Low Resource Sequence Tagging with Weak Labels.
Evaluating the Cross-Lingual Effectiveness of Massively Multilingual Neural Machine Translation.
Latent-Variable Non-Autoregressive Neural Machine Translation with Deterministic Inference Using a Delta Posterior.
Understanding Medical Conversations with Scattered Keyword Attention and Weak Supervision from Responses.
IntroVNMT: An Introspective Model for Variational Neural Machine Translation.
On the Generation of Medical Question-Answer Pairs.
Q-BERT: Hessian Based Ultra Low Precision Quantization of BERT.
Graph-Based Transformer with Cross-Candidate Verification for Semantic Parsing.
Are Noisy Sentences Useless for Distant Supervised Relation Extraction?
Automatic Fact-Guided Sentence Modification.
Interpretable Rumor Detection in Microblogs by Attending to User Interactions.
Can Embeddings Adequately Represent Medical Terminology? New Large-Scale Medical Term Similarity Datasets Have the Answer!
Rare Words: A Major Problem for Contextualized Embeddings and How to Fix it by Attentive Mimicking.
SensEmBERT: Context-Enhanced Sense Embeddings for Multilingual Word Sense Disambiguation.
CASIE: Extracting Cybersecurity Event Information from Text.
Hierarchical Reinforcement Learning for Open-Domain Dialog.
WinoGrande: An Adversarial Winograd Schema Challenge at Scale.
Getting Closer to AI Complete Question Answering: A Set of Prerequisite Real Tasks.
Probing Natural Language Inference Models through Semantic Fragments.
Multi-Task Learning with Generative Adversarial Training for Multi-Passage Machine Reading Comprehension.
Thinking Globally, Acting Locally: Distantly Supervised Global-to-Local Knowledge Selection for Background Based Conversation.
Towards Scalable Multi-Domain Conversational Agents: The Schema-Guided Dialogue Dataset.
Entrainment2Vec: Embedding Entrainment for Multi-Party Dialogues.
Generative Adversarial Zero-Shot Relational Learning for Knowledge Graphs.
DCR-Net: A Deep Co-Interactive Relation Network for Joint Dialog Act Recognition and Sentiment Classification.
Dynamic Knowledge Routing Network for Target-Guided Open-Domain Conversation.
Lexical Simplification with Pretrained Encoders.
Solving Sequential Text Classification as Board-Game Playing.
Translation-Based Matching Adversarial Network for Cross-Lingual Natural Language Inference.
Towards Building a Multilingual Sememe Knowledge Base: Predicting Sememes for BabelNet Synsets.
Verb Class Induction with Partial Supervision.
MTSS: Learn from Multiple Domain Teachers and Become a Multi-Domain Dialogue Expert.
Knowing What, How and Why: A Near Complete Solution for Aspect-Based Sentiment Analysis.
Associating Natural Language Comment and Source Code Entities.
Mask & Focus: Conversation Modelling by Learning Concepts.
Fine-Grained Entity Typing for Domain Independent Entity Linking.
Controlling Neural Machine Translation Formality with Synthetic Supervision.
AvgOut: A Simple Output-Probability Measure to Eliminate Dull Responses.
Deep Residual-Dense Lattice Network for Speech Enhancement.
Message Passing Attention Networks for Document Understanding.
Merging Weak and Active Supervision for Semantic Parsing.
Effective Modeling of Encoder-Decoder Architecture for Joint Entity and Relation Extraction.
Conclusion-Supplement Answer Generation for Non-Factoid Questions.
TRENDNERT: A Benchmark for Trend and Downtrend Detection in a Scientific Domain.
Enhancing Natural Language Inference Using New and Expanded Training Data Sets and New Learning Models.
RefNet: A Reference-Aware Network for Background Based Conversation.
Simplify-Then-Translate: Automatic Preprocessing for Black-Box Translation.
Robust Named Entity Recognition with Truecasing Pretraining.
CAWA: An Attention-Network for Credit Attribution.
Improving Question Generation with Sentence-Level Semantic Matching and Answer Position Inferring.
FPETS: Fully Parallel End-to-End Text-to-Speech System.
Graph-Based Reasoning over Heterogeneous External Knowledge for Commonsense Question Answering.
Hierarchical Contextualized Representation for Named Entity Recognition.
Attention-Informed Mixed-Language Training for Zero-Shot Cross-Lingual Task-Oriented Dialogue Systems.
CatGAN: Category-Aware Generative Adversarial Networks with Hierarchical Evolutionary Learning for Category Text Generation.
Synchronous Speech Recognition and Speech-to-Text Translation with Interactive Decoding.
Tensor Graph Convolutional Networks for Text Classification.
HAMNER: Headword Amplified Multi-Span Distantly Supervised Method for Domain Specific Named Entity Recognition.
A Robust Adversarial Training Approach to Machine Reading Comprehension.
Joint Character-Level Word Embedding and Adversarial Stability Training to Defend Adversarial Text.
Revision in Continuous Space: Unsupervised Text Style Transfer without Adversarial Learning.
Integrating Linguistic Knowledge to Sentence Paraphrase Generation.
Discovering New Intents via Constrained Deep Adaptive Clustering with Cluster Refinement.
Hierarchical Attention Network with Pairwise Loss for Chinese Zero Pronoun Resolution.
Semi-Supervised Learning on Meta Structure: Multi-Task Tagging and Parsing in Low-Resource Scenarios.
Embedding Compression with Isotropic Iterative Quantization.
MOSS: End-to-End Dialog System Framework with Modular Supervision.
Global Greedy Dependency Parsing.
Explicit Sentence Compression for Neural Machine Translation.
Complementary Auxiliary Classifiers for Label-Conditional Text Generation.
End-to-End Trainable Non-Collaborative Dialog System.
Neural Machine Translation with Joint Representation.
Span-Based Neural Buffer: Towards Efficient and Effective Utilization of Long-Distance Context for Neural Sequence Models.
Self-Attention Enhanced Selective Gate with Entity-Aware Embedding for Distantly Supervised Relation Extraction.
Towards Zero-Shot Learning for Automatic Phonemic Transcription.
Relevance-Promoting Language Model for Short-Text Conversation.
MetaMT, a Meta Learning Method Leveraging Multiple Domain Data for Low Resource Machine Translation.
Why Attention? Analyze BiLSTM Deficiency and Its Remedies in the Case of NER.
RobuTrans: A Robust Transformer-Based Text-to-Speech Model.
Simultaneous Learning of Pivots and Representations for Cross-Domain Sentiment Classification.
Cross-Lingual Low-Resource Set-to-Description Retrieval for Global E-Commerce.
Neuron Interaction Based Representation Composition for Neural Machine Translation.
Keywords-Guided Abstractive Sentence Summarization.
Aspect-Aware Multimodal Summarization for Chinese E-Commerce Products.
ICD Coding from Clinical Text Using Multi-Filter Residual Convolutional Neural Network.
GraphER: Token-Centric Entity Resolution with Graph Convolutional Neural Networks.
Recursively Binary Modification Model for Nested Named Entity Recognition.
ALOHA: Artificial Learning of Human Attributes for Dialogue Agents.
Segment-Then-Rank: Non-Factoid Question Answering on Instructional Videos.
Multi-Task Learning for Metaphor Detection with Graph Convolutional Neural Networks and Word Sense Disambiguation.
A General Framework for Implicit and Explicit Debiasing of Distributional Word Vector Spaces.
CSI: A Coarse Sense Inventory for 85% Word Sense Disambiguation.
Deep Attentive Ranking Networks for Learning to Order Sentences.
MA-DST: Multi-Attention-Based Scalable Dialog State Tracking.
Top-Down RST Parsing Utilizing Granularity Levels in Documents.
Modality-Balanced Models for Visual Dialogue.
QASC: A Dataset for Question Answering via Sentence Composition.
Infusing Knowledge into the Textual Entailment Task Using Graph Convolutional Networks.
Weakly Supervised POS Taggers Perform Poorly on Truly Low-Resource Languages.
Learning to Learn Morphological Inflection for Resource-Poor Languages.
Syntactically Look-Ahead Attention Network for Sentence Compression.
Monolingual Transfer Learning via Bilingual Translators for Style-Sensitive Paraphrase Generation.
Relation Extraction Exploiting Full Dependency Forests.
SemSUM: Semantic Dependency Guided Neural Abstractive Summarization.
Is BERT Really Robust? A Strong Baseline for Natural Language Attack on Text Classification and Entailment.
MMM: Multi-Stage Multi-Task Learning for Multi-Choice Reading Comprehension.
Real-Time Emotion Recognition via Attention Gated Hierarchical Memory Network.
Bayes-Adaptive Monte-Carlo Planning and Learning for Goal-Oriented Dialogues.
Privacy Enhanced Multimodal Neural Representations for Emotion Recognition.
MALA: Cross-Domain Dialogue Generation with Action Learning.
What Makes A Good Story? Designing Composite Rewards for Visual Storytelling.
Leveraging Multi-Token Entities in Document-Level Named Entity Recognition.
Knowledge-Enriched Visual Storytelling.
Unsupervised Interlingual Semantic Representations from Sentence Embeddings for Zero-Shot Cross-Lingual Transfer.
Emu: Enhancing Multilingual Sentence Embeddings with Semantic Specialization.
Improving Neural Relation Extraction with Positive and Unlabeled Learning.
Knowledge-Graph Augmented Word Representations for Named Entity Recognition.
Latent Relation Language Models.
Interactive Fiction Games: A Colossal Adventure.
One Homonym per Translation.
What Do You Mean 'Why?': Resolving Sluices in Conversations.
ManyModalQA: Modality Disambiguation and QA over Diverse Inputs.
CASE: Context-Aware Semantic Expansion.
P-SIF: Document Embeddings Using Partition Averaging.
Fact-Aware Sentence Split and Rephrase with Permutation Invariant Training.
Multi-Scale Self-Attention for Text Classification.
Fine-Tuning by Curriculum Learning for Non-Autoregressive Neural Machine Translation.
Multi-Source Domain Adaptation for Text Classification via DistanceNet-Bandits.
Working Memory-Driven Neural Networks with a Novel Knowledge Enhancement Paradigm for Implicit Discourse Relation Recognition.
Two Birds with One Stone: Investigating Invertible Neural Networks for Inverse Problems in Morphology.
A Large-Scale Dataset for Argument Quality Ranking: Construction and Analysis.
Two-Level Transformer and Auxiliary Coherence Modeling for Improved Text Segmentation.
Predictive Engagement: An Efficient Metric for Automatic Evaluation of Open-Domain Dialogue Systems.
TANDA: Transfer and Adapt Pre-Trained Transformer Models for Answer Sentence Selection.
Neural Snowball for Few-Shot Relation Learning.
Likelihood Ratios and Generative Classifiers for Unsupervised Out-of-Domain Detection in Task Oriented Dialog.
ABSent: Cross-Lingual Sentence Representation Mapping with Bidirectional GANs.
Open Domain Event Text Generation.
Document Summarization with VHTM: Variational Hierarchical Topic-Aware Mechanism.
Rethinking Generalization of Neural Models: A Named Entity Recognition Case Study.
Discontinuous Constituent Parsing with Pointer Networks.
Learning to Select Bi-Aspect Information for Document-Scale Text Content Manipulation.
Posterior-GAN: Towards Informative and Coherent Response Generation with Posterior Generative Adversarial Network.
Translucent Answer Predictions in Multi-Hop Reading Comprehension.
Latent Emotion Memory for Multi-Label Emotion Classification.
Corpus Wide Argument Mining - A Working Solution.
Detecting Asks in Social Engineering Attacks: Impact of Linguistic and Structural Knowledge.
Asymmetrical Hierarchical Networks with Attentive Interactions for Interpretable Review-Based Recommendation.
On Measuring and Mitigating Biased Inferences of Word Embeddings.
Joint Learning of Answer Selection and Answer Summary Generation in Community Question Answering.
An Iterative Polishing Framework Based on Quality Aware Masked Language Model for Chinese Poetry Generation.
Just Add Functions: A Neural-Symbolic Language Model.
Hypernym Detection Using Strict Partial Order Networks.
Adversarial Training Based Multi-Source Unsupervised Domain Adaptation for Sentiment Analysis.
Multiple Positional Self-Attention Network for Text Classification.
Discriminative Sentence Modeling for Story Ending Prediction.
Guiding Attention in Sequence-to-Sequence Models for Dialogue Act Prediction.
How to Ask Better Questions? A Large-Scale Multi-Domain Dataset for Rewriting Ill-Formed Questions.
An Empirical Study of Content Understanding in Conversational Question Answering.
Cross-Lingual Natural Language Generation via Pre-Training.
Dynamic Embedding on Textual Networks via a Gaussian Process.
Attending to Entities for Better Text Understanding.
Learning to Map Frequent Phrases to Sub-Structures of Meaning Representation for Neural Semantic Parsing.
TemPEST: Soft Template-Based Personalized EDM Subject Generation through Collaborative Summarization.
Improving Entity Linking by Modeling Latent Entity Type Information.
Schema-Guided Multi-Domain Dialogue State Tracking with Graph Attention Neural Networks.
Sequence Generation with Optimal-Transport-Enhanced Reinforcement Learning.
DMRM: A Dual-Channel Multi-Hop Reasoning Model for Visual Dialog.
Hyperbolic Interaction Model for Hierarchical Multi-Label Classification.
Zero-Shot Text-to-SQL Learning with Auxiliary Task.
Unsupervised Domain Adaptation on Reading Comprehension.
Learning from Easy to Complex: Adaptive Multi-Curricula Learning for Neural Dialogue Generation.
Graph Transformer for Graph-to-Sequence Learning.
Inducing Relational Knowledge from BERT.
Modelling Semantic Categories Using Conceptual Neighborhood.
Back to the Future - Temporal Adaptation of Text Representations.
PIQA: Reasoning about Physical Commonsense in Natural Language.
Generating Well-Formed Answers by Machine Reading with Stochastic Selector Networks.
Zero-Resource Cross-Lingual Named Entity Recognition.
Simultaneously Linking Entities and Extracting Relations from Biomedical Text without Mention-Level Supervision.
Understanding the Semantic Content of Sparse Word Embeddings Using a Commonsense Knowledge Base.
Fine-Grained Named Entity Typing over Distantly Supervised Data Based on Refined Representations.
Do Not Have Enough Data? Deep Learning to the Rescue!
Story Realization: Expanding Plot Events into Sentences.
End-to-End Argumentation Knowledge Graph Construction.
Modelling Sentence Pairs via Reinforcement Learning: An Actor-Critic Approach to Learn the Irrelevant Words.
Knowledge Distillation from Internal Representations.
LeDeepChef Deep Reinforcement Learning Agent for Families of Text-Based Games.
Beyond Trees: Analysis and Convergence of Belief Propagation in Graphs with Multiple Cycles.
Bi-Level Actor-Critic for Multi-Agent Coordination.
COBRA: Context-Aware Bernoulli Neural Networks for Reputation Assessment.
Optimal Common Contract with Heterogeneous Agents.
SMIX(λ): Enhancing Centralized Value Functions for Cooperative Multi-Agent Reinforcement Learning.
From Few to More: Large-Scale Dynamic Multiagent Curriculum Learning.
Shapley Q-Value: A Local Reward Approach to Solve Global Reward Games.
Generalized and Sub-Optimal Bipartite Constraints for Conflict-Based Search.
Fair Procedures for Fair Stable Marriage Outcomes.
Learning to Communicate Implicitly by Actions.
Arena: A General Evaluation Platform and Building Toolkit for Multi-Agent Intelligence.
Clouseau: Generating Communication Protocols from Commitments.
Multi-Agent Actor-Critic with Hierarchical Graph Attention Network.
Multi-Objective Multi-Agent Planning for Jointly Discovering and Tracking Mobile Objects.
Neighborhood Cognition Consistent Multi-Agent Reinforcement Learning.
Multi-Agent Game Abstraction via Graph Attention Neural Network.
A Variational Perturbative Approach to Planning in Graph-Based Markov Decision Processes.
Generative Attention Networks for Multi-Agent Behavioral Modeling.
Improving Policies via Search in Cooperative Partially Observable Games.
Distributed Machine Learning through Heterogeneous Edge Systems.
Distributed Stochastic Gradient Descent with Event-Triggered Communication.
Communication Learning via Backpropagation in Discrete Channels with Unknown Noise.
Implicit Coordination Using FOND Planning.
On the Convergence of Model Free Learning in Mean Field Games.
Parameterized Complexity of Envy-Free Resource Allocation in Social Networks.
Scalable Decision-Theoretic Planning in Open and Typed Multiagent Systems.
An Operational Semantics for True Concurrency in BDI Agent Systems.
A Particle Swarm Based Algorithm for Functional Distributed Constraint Optimization Problems.
Convergence of Opinion Diffusion is PSPACE-Complete.
AATEAM: Achieving the Ad Hoc Teamwork by Employing the Attention Mechanism.
HS-CAI: A Hybrid DCOP Algorithm via Combining Search with Context-Based Inference.
ODSS: Efficient Hybridization for Optimal Coalition Structure Generation.
Model Checking Temporal Epistemic Logic under Bounded Recall.
Learning the Value of Teamwork to Form Efficient Teams.
Incentive-Compatible Classification.
Partner Selection for the Emergence of Cooperation in Multi-Agent Systems Using Reinforcement Learning.
Parameterised Resource-Bounded ATL.
Subsidy Allocations in the Presence of Income Shocks.
Observe Before Play: Multi-Armed Bandit with Pre-Observations.
Semi-Supervised Streaming Learning with Emerging New Labels.
GSSNN: Graph Smoothing Splines Neural Networks.
A Knowledge-Aware Attentional Reasoning Network for Recommendation.
Object-Oriented Dynamics Learning through Multi-Level Abstraction.
Safe Sample Screening for Robust Support Vector Machine.
Posterior-Guided Neural Architecture Search.
Multi-View Spectral Clustering with Optimal Neighborhood Laplacian Matrix.
Side Information Dependence as a Regularizer for Analyzing Human Brain Conditions across Cognitive Experiments.
DGE: Deep Generative Network Embedding Based on Commonality and Individuality.
Deep Model-Based Reinforcement Learning via Estimated Uncertainty and Conservative Policy Optimization.
A Near-Optimal Change-Detection Based Algorithm for Piecewise-Stationary Combinatorial Semi-Bandits.
An Annotation Sparsification Strategy for 3D Medical Image Segmentation via Representative Selection and Self-Training.
Hearing Lips: Improving Lip Reading by Distilling Speech Recognizers.
Towards Query-Efficient Black-Box Adversary with Zeroth-Order Natural Gradient Descent.
Bridging Maximum Likelihood and Adversarial Learning via α-Divergence.
Online Second Price Auction with Semi-Bandit Feedback under the Non-Stationary Setting.
Hypergraph Label Propagation Network.
Joint Adversarial Learning for Domain Adaptation in Semantic Segmentation.
An Ordinal Data Clustering Algorithm with Automated Distance Learning.
Local Regularizer Improves Generalization.
Self-Paced Robust Learning for Leveraging Clean Labels in Noisy Data.
TapNet: Multivariate Time Series Classification with Attentional Prototypical Network.
Adaptive Double-Exploration Tradeoff for Outlier Detection.
AutoShrink: A Topology-Aware NAS for Discovering Efficient Neural Architecture.
Optimal Margin Distribution Learning in Dynamic Environments.
Atari-HEAD: Atari Human Eye-Tracking and Demonstration Dataset.
Variational Inference for Sparse Gaussian Process Modulated Hawkes Process.
High Performance Depthwise and Pointwise Convolutions on Mobile Devices.
Systematically Exploring Associations among Multivariate Data.
Universal Value Iteration Networks: When Spatially-Invariant Is Not Universal.
Policy Search by Target Distribution Learning for Continuous Control.
Learning from Positive and Unlabeled Data without Explicit Estimation of Class Prior.
CD-UAP: Class Discriminative Universal Adversarial Perturbation.
Aggregated Gradient Langevin Dynamics.
Topic Modeling on Document Networks with Adjacent-Encoder.
Fast Nonparametric Estimation of Class Proportions in the Positive-Unlabeled Classification Setting.
Apprenticeship Learning via Frank-Wolfe.
Trading-Off Static and Dynamic Regret in Online Least-Squares and Beyond.
Fragmentation Coagulation Based Mixed Membership Stochastic Blockmodel.
Divide-and-Conquer Learning with Nyström: Optimal Rate and Algorithm.
Shared Generative Latent Representation Learning for Multi-View Clustering.
A Novel Model for Imbalanced Data Classification.
Mastering Complex Control in MOBA Games with Deep Reinforcement Learning.
Efficient Neural Architecture Search via Proximal Iterations.
Graph Few-Shot Learning via Knowledge Transfer.
Dynamical System Inspired Adaptive Time Stepping Controller for Residual Network Families.
ML-LOO: Detecting Adversarial Examples with Feature Attribution.
Distributed Primal-Dual Optimization for Online Multi-Task Learning.
Harmonious Coexistence of Structured Weight Pruning and Ternarization for Deep Neural Networks.
Bi-Directional Generation for Unsupervised Domain Adaptation.
Revisiting Online Quantum State Learning.
Variational Adversarial Kernel Learned Imitation Learning.
Towards Accurate Low Bit-Width Quantization with Multiple Phase Adaptations.
Active Learning with Query Generation for Cost-Effective Text Classification.
Partial Label Learning with Batch Label Correction.
Effective Data Augmentation with Multi-Domain Learning GANs.
One-Shot Image Classification by Learning to Restore Prototypes.
Not All Attention Is Needed: Gated Attention Network for Sequence Data.
Light Multi-Segment Activation for Model Compression.
To Avoid the Pitfall of Missing Labels in Feature Selection: A Generative Model Gives the Answer.
Generative-Discriminative Complementary Learning.
Contextual-Bandit Based Personalized Recommendation with Time-Varying User Interests.
Partial Multi-Label Learning with Label Distribution.
Adversarial Domain Adaptation with Domain Mixup.
Deep Embedded Complementary and Interactive Information for Multi-View Classification.
Federated Patient Hashing.
Gromov-Wasserstein Factorization Models for Graph Clustering.
Learning Feature Interactions with Lorentzian Factorization Machine.
Infinite ShapeOdds: Nonparametric Bayesian Models for Shape Representations.
Partial Multi-Label Learning with Noisy Label Identification.
Efficient Projection-Free Online Methods with Stochastic Recursive Gradient.
Dual Adversarial Co-Learning for Multi-Domain Text Classification.
Multi-Label Causal Feature Selection.
SK-Net: Deep Learning on Point Cloud via End-to-End Discovery of Spatial Keypoints.
Regional Tree Regularization for Interpretability in Deep Neural Networks.
Meta-Amortized Variational Inference and Learning.
Estimating Early Fundraising Performance of Innovations via Graph-Based Market Environment Model.
Unified Graph and Low-Rank Tensor Learning for Multi-View Clustering.
Vector Quantization-Based Regularization for Autoencoders.
Characterizing Membership Privacy in Stochastic Gradient Langevin Dynamics.
ODIN: ODE-Informed Regression for Parameter and State Inference in Time-Continuous Dynamical Systems.
Towards Certificated Model Robustness Against Weight Perturbations.
Multi-View Multiple Clusterings Using Deep Matrix Factorization.
Less Is Better: Unweighted Data Subsampling via Influence Function.
Transparent Classification with Multilayer Logical Perceptrons and Random Binarization.
Attention-over-Attention Field-Aware Factorization Machine.
Non-Local U-Nets for Biomedical Image Segmentation.
An Objective for Hierarchical Clustering in Euclidean Space and Its Connection to Bisecting K-means.
Dynamic Network Pruning with Interpretable Layerwise Channel Selection.
Transductive Ensemble Learning for Neural Machine Translation.
Federated Latent Dirichlet Allocation: A Local Differential Privacy Based Framework.
Attention-Guide Walk Model in Heterogeneous Information Network for Multi-Style Recommendation Explanation.
Multi-Component Graph Convolutional Collaborative Filtering.
Intention Nets: Psychology-Inspired User Choice Behavior Modeling for Next-Basket Prediction.
Learning from Weak-Label Data: A Deep Forest Expedition.
Unsupervised Domain Adaptation via Structured Prediction Based Selective Pseudo-Labeling.
A Knowledge Transfer Framework for Differentially Private Sparse Learning.
Dual Relation Semi-Supervised Multi-Label Learning.
Differentially Private Learning with Small Public Data.
Crowdfunding Dynamics Tracking: A Reinforcement Learning Approach.
Reinforcement Learning with Perturbed Rewards.
Logo-2K+: A Large-Scale Logo Dataset for Scalable Logo Classification.
M-NAS: Meta Neural Architecture Search.
Incorporating Label Embedding and Feature Augmentation for Multi-Dimensional Classification.
Repetitive Reprediction Deep Decipher for Semi-Supervised Learning.
Adapting to Smoothness: A More Universal Algorithm for Online Convex Optimization.
Neural Cognitive Diagnosis for Intelligent Education Systems.
Compact Autoregressive Network.
Estimating Stochastic Linear Combination of Non-Linear Regressions.
SetRank: A Setwise Bayesian Approach for Collaborative Ranking from Implicit Feedback.
Learning General Latent-Variable Graphical Models with Predictive Belief Propagation.
Robust Self-Weighted Multi-View Projection Clustering.
Robust Tensor Decomposition via Orientation Invariant Tubal Nuclear Norms.
Reinforcement Learning Based Meta-Path Discovery in Large-Scale Heterogeneous Information Networks.
Fast and Efficient Boolean Matrix Factorization by Geometric Segmentation.
Justification-Based Reliability in Machine Learning.
Deep Conservative Policy Iteration.
Meta-Learning for Generalized Zero-Shot Learning.
Transfer Learning for Anomaly Detection through Localized and Unsupervised Instance Selection.
Learning to Crawl.
Order-Free Learning Alleviating Exposure Bias in Multi-Label Classification.
Differential Equation Units: Learning Functional Forms of Activation Functions from Data.
Sanity Checks for Saliency Metrics.
Network as Regularization for Training Deep Neural Networks: Framework, Model and Performance.
Building Calibrated Deep Models via Uncertainty Matching with Auxiliary Interval Predictors.
Scalable Variational Bayesian Kernel Selection for Sparse Gaussian Process Regression.
Bi-Objective Continual Learning: Learning 'New' While Consolidating 'Known'.
Discretizing Continuous Action Space for On-Policy Optimization.
Reborn Filters: Pruning Convolutional Neural Networks with Limited Data.
Beyond Dropout: Feature Map Distortion to Regularize Deep Neural Networks.
Joint Modeling of Local and Global Temporal Dynamics for Multivariate Time Series Forecasting with Missing Values.
Parameterized Indexed Value Function for Efficient Exploration in Reinforcement Learning.
Discriminative Adversarial Domain Adaptation.
Label Enhancement with Sample Correlations via Low-Rank Representation.
CGD: Multi-View Clustering via Cross-View Graph Diffusion.
Adversarial Transformations for Semi-Supervised Learning.
Revisiting Probability Distribution Assumptions for Information Theoretic Feature Selection.
Attentive Experience Replay.
Multi-Stage Self-Supervised Learning for Graph Convolutional Networks on Graphs with Few Labeled Nodes.
Stealthy and Efficient Adversarial Attacks against Deep Reinforcement Learning.
New Interpretations of Normalization Methods in Deep Learning.
Lifelong Spectral Clustering.
Learning Efficient Representations for Fake Speech Detection.
Scalable Probabilistic Matrix Factorization with Graph-Based Priors.
Benign Examples: Imperceptible Changes Can Enhance Image Translation Performance.
Infomax Neural Joint Source-Channel Coding via Adversarial Bit Flip.
Mega-Reward: Achieving Human-Level Play without Extrinsic Rewards.
Bivariate Beta-LSTM.
Aggregated Learning: A Vector-Quantization Approach to Learning Neural Network Classifiers.
Efficient Facial Feature Learning with Wide Ensemble-Based Convolutional Neural Networks.
Uncertainty-Aware Action Advising for Deep Reinforcement Learning Agents.
HLHLp: Quantized Neural Networks Training for Reaching Flat Minima in Loss Surface.
Hierarchically Clustered Representation Learning.
Morphism-Based Learning for Structured Data.
Block Hankel Tensor ARIMA for Multiple Short Time Series Forecasting.
Deep Message Passing on Sets.
Loss-Based Attention for Deep Multiple Instance Learning.
Quadruply Stochastic Gradient Method for Large Scale Nonlinear Semi-Supervised Ordinal Regression AUC Optimization.
Deep Time-Stream Framework for Click-through Rate Prediction by Tracking Interest Evolution.
Gamma-Nets: Generalizing Value Estimation over Timescale.
Revisiting Image Aesthetic Assessment via Self-Supervised Feature Learning.
Fractional Skipping: Towards Finer-Grained Dynamic CNN Inference.
Stable Learning via Sample Reweighting.
AUC Optimization with a Reject Option.
Transfer Value Iteration Networks.
Adaptive Trust Region Policy Optimization: Global Convergence and Faster Rates for Regularized MDPs.
Improved PAC-Bayesian Bounds for Linear Regression.
Online Active Learning of Reject Option Classifiers.
Sequential Mode Estimation with Oracle Queries.
Universal Adversarial Training.
Empirical Bounds on Linear Regions of Deep Rectifier Networks.
Uncertainty-Aware Deep Classifiers Using Generative Models.
Learning Counterfactual Representations for Estimating Individual Dose-Response Curves.
Graph Representation Learning via Ladder Gamma Variational Autoencoders.
Weighted Sampling for Combined Model Selection and Hyperparameter Tuning.
Rank3DGAN: Semantic Mesh Generation Using Relative Attributes.
Random Intersection Graphs and Missing Data.
Weakly Supervised Sequence Tagging from Noisy Rules.
Chained Representation Cycling: Learning to Estimate 3D Human Pose and Shape by Cycling Between Representations.
Linear Context Transform Block.
Generative Continual Concept Learning.
Actionable Ethics through Neural Learning.
Ensembles of Locally Independent Prediction Models.
On the Role of Weight Sharing During Deep Option Learning.
Fairness for Robust Log Loss Classification.
Delay-Adaptive Distributed Stochastic Optimization.
DARB: A Density-Adaptive Regular-Block Pruning for Deep Neural Networks.
Optimizing Nondecomposable Data Dependent Regularizers via Lagrangian Reparameterization Offers Significant Performance and Efficiency Gains.
Abstract Interpretation of Decision Tree Ensemble Classifiers.
ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations.
Synthesizing Action Sequences for Modifying Model Decisions.
How Should an Agent Practice?
A New Burrows Wheeler Transform Markov Distance.
Temporal Network Embedding with High-Order Nonlinear Information.
Stochastic Approximate Gradient Descent via the Langevin Algorithm.
Diversified Bayesian Nonnegative Matrix Factorization.
CAG: A Real-Time Low-Cost Enhanced-Robustness High-Transferability Content-Aware Adversarial Attack Generator.
Generalized Hidden Parameter MDPs: Transferable Model-Based RL in a Handful of Trials.
A Bayesian Approach for Estimating Causal Effects from Observational Data.
Motif-Matching Based Subgraph-Level Attentional Convolutional Network for Graph Classification.
Achieving Fairness in the Stochastic Multi-Armed Bandit Problem.
Unsupervised Attributed Multiplex Network Embedding.
EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs.
Scaling All-Goals Updates in Reinforcement Learning Using Convolutional Neural Networks.
Adversarial Localized Energy Network for Structured Prediction.
Overcoming Catastrophic Forgetting by Neuron-Level Plasticity Control.
Linear Bandits with Feature Feedback.
Uncorrected Least-Squares Temporal Difference with Lambda-Return.
Cut-Based Graph Learning Networks to Discover Compositional Structure of Sequential Video Data.
Weighted Automata Extraction from Recurrent Neural Networks via Regression on State Spaces.
Radial and Directional Posteriors for Bayesian Deep Learning.
Maximum Likelihood Embedding of Logistic Random Dot Product Graphs.
Brain-Mediated Transfer Learning of Convolutional Neural Networks.
On the Anatomy of MCMC-Based Maximum Likelihood Learning of Energy-Based Models.
Reliable Multilabel Classification: Prediction with Partial Abstention.
Bayesian Optimization for Categorical and Category-Specific Continuous Inputs.
Pairwise Fairness for Ranking and Regression.
Efficiently Enumerating Substrings with Statistically Significant Frequencies of Locally Optimal Occurrences in Gigantic String.
An Intrinsically-Motivated Approach for Learning Highly Exploring and Fast Mixing Policies.
Learning Weighted Model Integration Distributions.
Self-Supervised Learning for Generalizable Out-of-Distribution Detection.
Metareasoning in Modular Software Systems: On-the-Fly Configuration Using Reinforcement Learning with Rich Contextual Representations.
On Adaptivity in Information-Constrained Online Learning.
Improved Knowledge Distillation via Teacher Assistant.
Differentiable Reasoning on Large Knowledge Bases and Natural Language.
Deep Embedded Non-Redundant Clustering.
Regularized Wasserstein Means for Aligning Distributional Data.
Neural Inheritance Relation Guided One-Shot Layer Assignment Search.
Multi-Zone Unit for Recurrent Neural Networks.
Learning Agent Communication under Limited Bandwidth by Message Pruning.
Graph-Hist: Graph Classification from Latent Feature Histograms with Application to Bot Detection.
Count-Based Exploration with the Successor Representation.
PCONV: The Missing but Desirable Sparsity in DNN Weight Pruning for Real-Time Execution on Mobile Devices.
Reinforcement Learning from Imperfect Demonstrations under Soft Expert Guidance.
Particle Filter Recurrent Neural Networks.
Projective Quadratic Regression for Online Learning.
The HSIC Bottleneck: Deep Learning without Back-Propagation.
Online Planner Selection with Graph Neural Networks and Adaptive Scheduling.
Adversarial Dynamic Shapelet Networks.
Temporal Pyramid Recurrent Neural Network.
Inefficiency of K-FAC for Large Batch Size Training.
Memory Augmented Graph Neural Networks for Sequential Recommendation.
Fastened CROWN: Tightened Neural Network Robustness Certificates.
Unsupervised Domain Adaptation via Discriminative Manifold Embedding and Alignment.
Learning from the Past: Continual Meta-Learning with Bayesian Graph Neural Networks.
Enhancing Nearest Neighbor Based Entropy Estimator for High Dimensional Distributions via Bootstrapping Local Ellipsoid.
Structured Output Learning with Conditional Generative Flows.
Cost-Effective Incentive Allocation via Structured Counterfactual Inference.
Structured Sparsification of Gated Recurrent Neural Networks.
Incentivized Exploration for Multi-Armed Bandits under Reward Drift.
Towards Fine-Grained Temporal Network Representation via Time-Reinforced Random Walk.
Interactive Rare-Category-of-Interest Mining from Large Datasets.
Uncertainty Aware Graph Gaussian Process for Semi-Supervised Learning.
Collaborative Sampling in Generative Adversarial Networks.
IPO: Interior-Point Policy Optimization under Constraints.
Diversified Interactive Recommendation with Implicit Feedback.
Adaptive Activation Network and Functional Regularization for Efficient and Flexible Deep Multi-Task Learning.
Independence Promoted Graph Disentangled Networks.
Weighted-Sampling Audio Adversarial Example Attack.
Layerwise Sparse Coding for Pruned Deep Neural Networks with Extreme Compression Ratio.
An ADMM Based Framework for AutoML Pipeline Configuration.
Stochastic Loss Function.
AutoCompress: An Automatic DNN Structured Pruning Framework for Ultra-High Compression Rates.
Attribute Propagation Network for Graph Zero-Shot Learning.
A Cluster-Weighted Kernel K-Means Method for Multi-View Clustering.
EC-GAN: Inferring Brain Effective Connectivity via Generative Adversarial Networks.
Random Fourier Features via Fast Surrogate Leverage Weighted Sampling.
OOGAN: Disentangling GAN with One-Hot Sampling and Orthogonal Regularization.
Differentiable Algorithm for Marginalising Changepoints.
Instance Enhancement Batch Normalization: An Adaptive Regulator of Batch Noise.
LMLFM: Longitudinal Multi-Level Factorization Machine.
Tensor Completion for Weakly-Dependent Data on Graph for Metro Passenger Flow Prediction.
Adaptive Two-Dimensional Embedded Image Clustering.
Learning to Auto Weight: Entirely Data-Driven and Highly Efficient Weighting Framework.
RTN: Reparameterized Ternary Network.
Learning Signed Network Embedding via Graph Attention.
Efficient Automatic CASH via Rising Bandits.
A Forest from the Trees: Generation through Neighborhoods.
IVFS: Simple and Efficient Feature Selection for High Dimensional Topology Preservation.
On the Learning Property of Logistic and Softmax Losses for Deep Neural Networks.
FlowScope: Spotting Money Laundering Based on Graphs.
Do Subsampled Newton Methods Work for High-Dimensional Data?
Understanding the Disharmony between Weight Normalization Family and Weight Decay.
Neural Graph Embedding for Neural Architecture Search.
Tweedie-Hawkes Processes: Interpreting the Phenomena of Outbreaks.
Co-GCN for Multi-View Semi-Supervised Learning.
Relation Inference among Sensor Time Series in Smart Buildings with Metric Learning.
Stochastic Online Learning with Probabilistic Graph Feedback.
Coupled-View Deep Classifier Learning from Multiple Noisy Annotators.
Solving General Elliptical Mixture Models through an Approximate Wasserstein Manifold.
New Efficient Multi-Spike Learning for Fast Processing and Robust Learning.
Practical Federated Gradient Boosting Decision Trees.
Symmetric Metric Learning with Adaptive Margin for Recommendation.
Graph Attention Based Proposal 3D ConvNets for Action Detection.
Automated Spectral Kernel Learning.
Infrared-Visible Cross-Modal Person Re-Identification with an X Modality.
Beyond Unfolding: Exact Recovery of Latent Convex Tensor Decomposition Under Reshuffling.
Stochastically Robust Personalized Ranking for LSH Recommendation Retrieval.
Robustness Certificates for Sparse Adversarial Attacks by Randomized Ablation.
Spatiotemporally Constrained Action Space Attacks on Deep Reinforcement Learning Agents.
URNet: User-Resizable Residual Networks with Conditional Gating Module.
Monte-Carlo Tree Search in Continuous Action Spaces with Value Gradients.
Residual Continual Learning.
Residual Neural Processes.
Proximity Preserving Binary Code Using Signed Graph-Cut.
A Simple and Efficient Tensor Calculus.
Improved Subsampled Randomized Hadamard Transform for Linear SVM.
Correcting Predictions for Approximate Bayesian Inference.
Google Research Football: A Novel Reinforcement Learning Environment.
Learning MAX-SAT from Contextual Examples for Combinatorial Optimisation.
Stable Prediction with Model Misspecification and Agnostic Distribution Shift.
Specifying Weight Priors in Bayesian Deep Neural Networks with Empirical Bayes.
Learning Student Networks with Few Data.
A Unified Framework for Knowledge Intensive Gradient Boosting: Leveraging Human Experts for Noisy Sparse Domains.
Plug-in, Trainable Gate for Streamlining Arbitrary Neural Networks.
Options of Interest: Temporal Abstraction with Interest Functions.
Being Optimistic to Be Conservative: Quickly Learning a CVaR Policy.
Gradient Boosts the Approximate Vanishing Ideal.
Nonlinear System Identification via Tensor Completion.
Large-Scale Multi-View Subspace Clustering in Linear Time.
Towards Oracle Knowledge Distillation with Neural Architecture Search.
Absum: Simple Regularization Method for Reducing Structural Sensitivity of Convolutional Neural Networks.
More Accurate Learning of k-DNF Reference Classes.
InvNet: Encoding Geometric and Statistical Invariances in Deep Generative Models.
Dynamic Instance Normalization for Arbitrary Style Transfer.
GraLSP: Graph Neural Networks with Local Structural Patterns.
Rank Aggregation via Heterogeneous Thurstone Preference Models.
Long Short-Term Sample Distillation.
Generative Exploration and Exploitation.
Algorithmic Improvements for Deep Reinforcement Learning Applied to Interactive Fiction.
Representation Learning with Multiple Lipschitz-Constrained Alignments on Partially-Labeled Cross-Domain Data.
Maximum Margin Multi-Dimensional Classification.
Sequential Recommendation with Relation-Aware Kernelized Self-Attention.
DefogGAN: Predicting Hidden Information in the StarCraft Fog of War with Generative Adversarial Nets.
An Efficient Explorative Sampling Considering the Generative Boundaries of Deep Generative Neural Networks.
Bounding Regret in Empirical Games.
Invariant Representations through Adversarial Forgetting.
Maximizing Overall Diversity for Improved Uncertainty Estimates in Deep Ensembles.
Class Prior Estimation with Biased Positives and Unlabeled Examples.
Co-Occurrence Estimation from Aggregated Data with Auxiliary Information.
Semi-Supervised Learning for Maximizing the Partial AUC.
Word-Level Contextual Sentiment Analysis with Interpretability.
Control Flow Graph Embedding Based on Multi-Instance Decomposition for Bug Localization.
Collaborative Graph Convolutional Networks: Unsupervised Learning Meets Semi-Supervised Learning.
DIANet: Dense-and-Implicit Attention Network.
Meta-Learning PAC-Bayes Priors in Model Averaging.
Feature Variance Regularization: A Simple Way to Improve the Generalizability of Neural Networks.
Unsupervised Nonlinear Feature Selection from High-Dimensional Signed Networks.
DWM: A Decomposable Winograd Method for Convolution Acceleration.
Towards Interpretation of Pairwise Learning.
Query-Driven Multi-Instance Learning.
TellTail: Fast Scoring and Detection of Dense Subgraphs.
End-to-End Unpaired Image Denoising with Conditional Adversarial Networks.
An Attention-Based Graph Neural Network for Heterogeneous Structural Learning.
Reasoning on Knowledge Graphs with Debate Dynamics.
Eigenvalue Normalized Recurrent Neural Networks for Short Term Memory.
EPOC: Efficient Perception via Optimal Communication.
Heterogeneous Transfer Learning with Weighted Instance-Correspondence Data.
SNEQ: Semi-Supervised Attributed Network Embedding with Attention-Based Quantisation.
Interpretable and Differentially Private Predictions.
Robust Federated Learning via Collaborative Machine Teaching.
High Tissue Contrast MRI Synthesis Using Multi-Stage Attention-GAN for Segmentation.
AdaFilter: Adaptive Filter Fine-Tuning for Deep Transfer Learning.
IWE-Net: Instance Weight Network for Locating Negative Comments and its application to improve Traffic User Experience.
Nonlinear Mixup: Out-Of-Manifold Data Augmentation for Text Classification.
Robust Stochastic Bandit Algorithms under Probabilistic Unbounded Adversarial Attack.
AlignFlow: Cycle Consistent Learning from Multiple Domains via Normalizing Flows.
Potential Passenger Flow Prediction: A Novel Study for Urban Transportation Development.
Online Metric Learning for Multi-Label Classification.
Robust Gradient-Based Markov Subsampling.
Adversarially Robust Distillation.
Diachronic Embedding for Temporal Knowledge Graph Completion.
Reinforcement Learning with Non-Markovian Rewards.
Modeling Dialogues with Hashcode Representations: A Nonparametric Approach.
Improved Algorithms for Conservative Exploration in Bandits.
Revisiting Bilinear Pooling: A Coding Perspective.
A Multi-Channel Neural Graphical Event Model with Negative Evidence.
Cross-Modal Subspace Clustering via Deep Canonical Correlation Analysis.
Tensor-SVD Based Graph Learning for Multi-View Subspace Clustering.
Infinity Learning: Learning Markov Chains from Aggregate Steady-State Observations.
Adaptive Convolutional ReLUs.
On the Parameterized Complexity of Clustering Incomplete Data into Subspaces of Small Rank.
Fast and Deep Graph Neural Networks.
Induction of Subgoal Automata for Reinforcement Learning.
Training Decision Trees as Replacement for Convolution Layers.
Learning Triple Embeddings from Knowledge Graphs.
Privacy-Preserving Gaussian Process Regression - A Modular Approach to the Application of Homomorphic Encryption.
Regularized Training and Tight Certification for Randomized Smoothed Classifier with Provable Robustness.
Distributionally Robust Counterfactual Risk Minimization.
Polynomial Matrix Completion for Missing Data Imputation and Transductive Learning.
Unsupervised Metric Learning with Synthetic Examples.
An Information-Theoretic Quantification of Discrimination with Exempt Features.
On the Discrepancy between the Theoretical Analysis and Practical Implementations of Compressed Communication for Distributed Deep Learning.
Fairness in Network Representation by Latent Structural Heterogeneity in Observational Data.
Gradient-Aware Model-Based Policy Search.
Improving the Robustness of Wasserstein Embedding by Adversarial PAC-Bayesian Learning.
Integrating Overlapping Datasets Using Bivariate Causal Discovery.
Optimizing Discrete Spaces via Expensive Evaluations: A Learning to Search Framework.
Reinforcing Neural Network Stability with Attractor Dynamics.
System Identification with Time-Aware Neural Sequence Models.
Capsule Routing via Variational Bayes.
Fixed-Horizon Temporal Difference Methods for Stable Reinforcement Learning.
Making Existing Clusterings Fairer: Algorithms, Complexity Results and Insights.
DNNs as Layers of Cooperating Classifiers.
A Skip-Connected Evolving Recurrent Neural Network for Data Stream Classification under Label Latency Scenario.
Explainable Data Decompositions.
A Tale of Two-Timescale Reinforcement Learning with the Tightest Finite-Time Bound.
Label Error Correction and Generation through Label Relationships.
Exploiting Spatial Invariance for Scalable Unsupervised Object Tracking.
Forgetting to Learn Logic Programs.
Representing Closed Transformation Paths in Encoded Network Latent Space.
A Constraint-Based Approach to Learning and Explanation.
Deep Mixed Effect Model Using Gaussian Processes: A Personalized and Reliable Prediction for Healthcare.
Active Learning in the Geometric Block Model.
A General Approach to Fairness with Optimal Transport.
Suspicion-Free Adversarial Attacks on Clustering Algorithms.
Time2Graph: Revisiting Time Series Modeling with Dynamic Shapelets.
Adaptive Factorization Network: Learning Adaptive-Order Feature Interactions.
Seq2Sick: Evaluating the Robustness of Sequence-to-Sequence Models with Adversarial Examples.
Towards Better Forecasting by Fusing Near and Distant Future Visions.
Distilling Portable Generative Adversarial Networks for Image Translation.
InstaNAS: Instance-Aware Neural Architecture Search.
Semi-Supervised Learning under Class Distribution Mismatch.
Compressed Self-Attention for Deep Metric Learning.
Multi-View Partial Multi-Label Learning with Graph-Based Disambiguation.
Optimal Attack against Autoregressive Models by Manipulating the Environment.
AutoDAL: Distributed Active Learning with Automatic Hyperparameter Selection.
Multi-Range Attentive Bicomponent Graph Convolutional Network for Traffic Forecasting.
Adversarial-Learned Loss for Domain Adaptation.
Multi-View Clustering in Latent Embedding Space.
Outlier Detection Ensemble with Embedded Feature Selection.
Weakly Supervised Disentanglement by Pairwise Similarities.
A Frank-Wolfe Framework for Efficient and Effective Adversarial Attacks.
Variational Metric Scaling for Metric-Based Meta-Learning.
Fast Adaptively Weighted Matrix Factorization for Recommendation with Implicit Feedback.
Generative Adversarial Networks for Video-to-Video Domain Adaptation.
LS-Tree: Model Interpretation When the Data Are Linguistic.
ECGadv: Generating Adversarial Electrocardiogram to Misguide Arrhythmia Classification System.
Measuring and Relieving the Over-Smoothing Problem for Graph Neural Networks from the Topological View.
Online Knowledge Distillation with Diverse Peers.
HoMM: Higher-Order Moment Matching for Unsupervised Domain Adaptation.
Toward A Thousand Lights: Decentralized Deep Reinforcement Learning for Large-Scale Traffic Signal Control.
A New Ensemble Adversarial Attack Powered by Long-Term Gradient Memories.
Robust Data Programming with Precision-guided Labeling Functions.
A Restricted Black-Box Adversarial Framework Towards Attacking Graph Embedding Models.
Reinforcement Learning When All Actions Are Not Always Available.
Lifelong Learning with a Changing Action Set.
Asking the Right Questions to the Right Users: Active Learning with Imperfect Oracles.
Exponential Family Graph Embeddings.
Generalization Error Bounds of Gradient Descent for Learning Over-Parameterized Deep ReLU Networks.
Fatigue-Aware Bandits for Dependent Click Models.
Active Ordinal Querying for Tuplewise Similarity Learning.
Predicting Propositional Satisfiability via End-to-End Learning.
Deterministic Value-Policy Gradients.
A Multi-Scale Approach for Graph Link Prediction.
Information-Theoretic Understanding of Population Risk Improvement with Model Compression.
Efficient Verification of ReLU-Based Neural Networks via Dependency Analysis.
Proximal Distilled Evolutionary Reinforcement Learning.
A Stochastic Derivative-Free Optimization Method with Importance Sampling: Theory and Learning to Control.
An Efficient Evolutionary Algorithm for Subset Selection with General Cost Constraints.
Event-Driven Continuous Time Bayesian Networks.
Exploratory Combinatorial Optimization with Reinforcement Learning.
Midas: Microcluster-Based Detector of Anomalies in Edge Streams.
Scalable Attentive Sentence Pair Modeling via Distilled Sentence Embedding.
Learning to Optimize Computational Resources: Frugal Training with Generalization Guarantees.
Learning-Based Efficient Graph Similarity Computation via Multi-Scale Convolutional Set Matching.
A Three-Level Optimization Model for Nonlinearly Separable Clustering.
Few Shot Network Compression via Cross Distillation.
Efficient Inference of Optimal Decision Trees.
Kriging Convolutional Networks.
An Implicit Form of Krasulina's k-PCA Update without the Orthonormality Constraint.
Pursuit of Low-Rank Models of Time-Varying Matrices Robust to Sparse and Measurement Noise.
Exact and Efficient Inference for Collective Flow Diffusion Model via Minimum Convex Cost Flow Algorithm.
Detecting Semantic Anomalies.
Learning Optimal Decision Trees Using Caching Branch-and-Bound Search.
Bounds and Complexity Results for Learning Coalition-Based Interaction Functions in Networked Social Systems.
DeGAN: Data-Enriching GAN for Retrieving Representative Samples from a Trained Classifier.
Image-Adaptive GAN Based Reconstruction.
Indirect Stochastic Gradient Quantization and Its Application in Distributed Deep Learning.
Quantized Compressive Sampling of Stochastic Gradients for Efficient Communication in Distributed Deep Learning.
Learning to Reason: Leveraging Neural Networks for Approximate DNF Counting.
LTLƒ Synthesis with Fairness and Stability Assumptions.
Deciding the Loosely Guarded Fragment and Querying Its Horn Fragment Using Resolution.
A Practical Approach to Forgetting in Description Logics with Nominals.
Learning Hierarchy-Aware Knowledge Graph Embeddings for Link Prediction.
On the Expressivity of ASK Queries in SPARQL.
Towards Universal Languages for Tractable Ontology Mediated Query Answering.
Few-Shot Knowledge Graph Completion.
Ranking-Based Semantics for Sets of Attacking Arguments.
COTSAE: CO-Training of Structure and Attribute Embeddings for Entity Alignment.
Query Answering with Guarded Existential Rules under Stable Model Semantics.
InteractE: Improving Convolution-Based Knowledge Graph Embeddings by Increasing Feature Interactions.
Contextual Parameter Generation for Knowledge Graph Link Prediction.
Adversarial Deep Network Embedding for Cross-Network Node Classification.
A Framework for Measuring Information Asymmetry.
Relatedness and TBox-Driven Rule Learning in Large Knowledge Bases.
Graph Representations for Higher-Order Logic and Theorem Proving.
Learning Query Inseparable εℒℋ Ontologies.
Rule-Guided Compositional Representation Learning on Knowledge Graphs.
Deciding Acceptance in Incomplete Argumentation Frameworks.
Blameworthiness in Security Games.
Commonsense Knowledge Base Completion with Structural and Semantic Context.
Resilient Logic Programs: Answer Set Programs Challenged by Ontologies.
Explanations for Inconsistency-Tolerant Query Answering under Existential Rules.
K-BERT: Enabling Language Representation with Knowledge Graph.
Path Ranking with Attention to Type Hierarchies.
Automatic Verification of Liveness Properties in the Situation Calculus.
FastLAS: Scalable Inductive Logic Programming Incorporating Domain-Specific Optimisation Criteria.
Logics for Sizes with Union or Intersection.
Complexity and Expressive Power of Disjunction and Negation in Limit Datalog.
Least General Generalizations in Description Logic: Verification and Existence.
Aggregation of Perspectives Using the Constellations Approach to Probabilistic Argumentation.
Going Deep: Graph Convolutional Ladder-Shape Networks.
Structural Decompositions of Epistemic Logic Programs.
Proportional Belief Merging.
Efficient Model-Based Diagnosis of Sequential Circuits.
ElGolog: A High-Level Programming Language with Memory of the Execution History.
Hypothetical Answers to Continuous Queries over Data Streams.
Epistemic Integrity Constraints for Ontology-Based Data Management.
Answering Conjunctive Queries with Inequalities in DL-Liteℛ.
ParamE: Regarding Neural Network Parameters as Relation Embeddings for Knowledge Graph Completion.
Model-Based Diagnosis with Uncertain Observations.
Checking Chase Termination over Ontologies of Existential Rules with Equality.
Forgetting an Argument.
Revisiting the Foundations of Abstract Argumentation - Semantics Based on Weak Admissibility and Weak Defense.
Query Rewriting for Ontology-Mediated Conditional Answers.
Learning and Reasoning for Robot Sequential Decision Making under Uncertainty.
Crowd-Assisted Disaster Scene Assessment with Human-AI Interactive Attention.
Variational Pathway Reasoning for EEG Emotion Recognition.
Instance-Adaptive Graph for EEG Emotion Recognition.
Reinforcing an Image Caption Generator Using Off-Line Human Feedback.
Towards Socially Responsible AI: Cognitive Bias-Aware Multi-Objective Learning.
UCF-STAR: A Large Scale Still Image Dataset for Understanding Human Actions.
Learning Graph Convolutional Network for Skeleton-Based Human Action Recognition by Neural Searching.
Multi-Source Domain Adaptation for Visual Sentiment Classification.
Graph-Based Decoding Model for Functional Alignment of Unaligned fMRI Data.
Harnessing GANs for Zero-Shot Learning of New Classes in Visual Speech Recognition.
GaSPing for Utility.
Conditional Generative Neural Decoding with Structured CNN Feature Prediction.
MIMAMO Net: Integrating Micro- and Macro-Motion for Video Emotion Recognition.
Regression under Human Assistance.
Towards Awareness of Human Relational Strategies in Virtual Agents.
CoCoX: Generating Conceptual and Counterfactual Explanations via Fault-Lines.
Fine-Grained Machine Teaching with Attention Modeling.
HirePeer: Impartial Peer-Assessed Hiring at Scale in Expert Crowdsourcing Markets.
Cost-Accuracy Aware Adaptive Labeling for Active Learning.
BAR - A Reinforcement Learning Agent for Bounding-Box Automated Refinement.
Querying to Find a Safe Policy under Uncertain Safety Constraints in Markov Decision Processes.
CG-GAN: An Interactive Evolutionary GAN-Based Approach for Facial Composite Generation.
Learning to Interactively Learn and Assist.
Corpus-Level End-to-End Exploration for Interactive Systems.
Hierarchical Expertise-Level Modeling for User Specific Robot-Behavior Explanations.
Human-Machine Collaboration for Fast Land Cover Mapping.
Relative Attributing Propagation: Interpreting the Comparative Contributions of Individual Units in Deep Neural Networks.
Explainable Reinforcement Learning through a Causal Lens.
What Is It You Really Want of Me? Generalized Reward Learning with Biased Beliefs about Domain Dynamics.
A Framework for Engineering Human/Agent Teaming Systems.
Asymptotically Unambitious Artificial General Intelligence.
Just Ask: An Interactive Learning Framework for Vision and Language Navigation.
A Human-AI Loop Approach for Joint Keyword Discovery and Expectation Estimation in Micropost Event Detection.
Enumerating Maximal k-Plexes with Worst-Case Time Guarantee.
Reduction and Local Search for Weighted Graph Coloring Problem.
Trading Convergence Rate with Computational Budget in High Dimensional Bayesian Optimization.
Asymptotic Risk of Bézier Simplex Fitting.
Subset Selection by Pareto Optimization with Recombination.
Cakewalk Sampling.
A Learning Based Branch and Bound for Maximum Common Subgraph Related Problems.
On Performance Estimation in Automatic Algorithm Configuration.
How the Duration of the Learning Period Affects the Performance of Random Gradient Selection Hyper-Heuristics.
Learning to Optimize Variational Quantum Circuits to Solve Combinatorial Problems.
Runtime Analysis of Somatic Contiguous Hypermutation Operators in MOEA/D Framework.
Envelope-Based Approaches to Real-Time Heuristic Search.
Local Search with Dynamic-Threshold Configuration Checking and Incremental Neighborhood Updating for Maximum k-plex Problem.
An Interactive Regret-Based Genetic Algorithm for Solving Multi-Objective Combinatorial Optimization Problems.
A Unifying View on Individual Bounds and Heuristic Inaccuracies in Bidirectional Search.
Computing Team-Maxmin Equilibria in Zero-Sum Multiplayer Extensive-Form Games.
Computing Equilibria in Binary Networked Public Goods Games.
Algorithms for Manipulating Sequential Allocation.
A Multi-Unit Profit Competitive Mechanism for Cellular Traffic Offloading.
Deep Learning-Powered Iterative Combinatorial Auctions.
Bounded Incentives in Manipulating the Probabilistic Serial Rule.
Nice Invincible Strategy for the Average-Payoff IPD.
Multi-Type Resource Allocation with Partial Preferences.
Path Planning Problems with Side Observations - When Colonels Play Hide-and-Seek.
Complexity of Computing the Shapley Value in Games with Externalities.
Reinforcement Mechanism Design: With Applications to Dynamic Pricing in Sponsored Search Auctions.
Solving Online Threat Screening Games using Constrained Action Space Reinforcement Learning.
Comparing Election Methods Where Each Voter Ranks Only Few Candidates.
Balancing the Tradeoff between Profit and Fairness in Rideshare Platforms during High-Demand Hours.
Practical Frank-Wolfe Method with Decision Diagrams for Computing Wardrop Equilibrium of Combinatorial Congestion Games.
Robust Market Equilibria with Uncertain Preferences.
Price of Fairness in Budget Division and Probabilistic Social Choice.
Can We Predict the Election Outcome from Sampled Votes?
The Surprising Power of Hiding Information in Facility Location.
The Effectiveness of Peer Prediction in Long-Term Forecasting.
Lifting Preferences over Alternatives to Preferences over Sets of Alternatives: The Complexity of Recognizing Desirable Families of Sets.
Mechanism Design with Predicted Task Revenue for Bike Sharing Systems.
Limitations of Incentive Compatibility on Discrete Type Spaces.
Adaptive Quantitative Trading: An Imitative Deep Reinforcement Learning Approach.
Structure Learning for Approximate Solution of Many-Player Games.
Defending with Shared Resources on a Network.
Perpetual Voting: Fairness in Long-Term Decision Making.
Information Elicitation Mechanisms for Statistical Estimation.
Communication, Distortion, and Randomness in Metric Voting.
An Analysis Framework for Metric Voting based on LP Duality.
On the Max-Min Fair Stochastic Allocation of Indivisible Goods.
Strategy-Proof and Non-Wasteful Multi-Unit Auction via Social Network.
Double-Oracle Sampling Method for Stackelberg Equilibrium Approximation in General-Sum Extensive-Form Games.
A Multiarmed Bandit Based Incentive Mechanism for a Subset Selection of Customers for Demand Response in Smart Grids.
Repeated Multimarket Contact with Private Monitoring: A Belief-Free Approach.
A Simple, Fast, and Safe Mediator for Congestion Management.
Model and Reinforcement Learning for Markov Games with Risk Preferences.
Fair Division Through Information Withholding.
The Complexity of Computing Maximin Share Allocations on Graphs.
Strongly Budget Balanced Auctions for Multi-Sided Markets.
Contiguous Cake Cutting: Hardness Results and Approximation Algorithms.
Beyond Pairwise Comparisons in Social Choice: A Setwise Kemeny Aggregation Problem.
Bidding in Smart Grid PDAs: Theory, Analysis and Strategy.
VCG under Sybil (False-Name) Attacks - A Bayesian Analysis.
Preventing Arbitrage from Collusion When Eliciting Probabilities.
Strategyproof Mechanisms for Friends and Enemies Games.
Designing Committees for Mitigating Biases.
Coarse Correlation in Extensive-Form Games.
Iterative Delegations in Liquid Democracy with Restricted Preferences.
Analysis of One-to-One Matching Mechanisms via SAT Solving: Impossibilities for Universal Axioms.
On Swap Convexity of Voting Rules.
Manipulating Districts to Win Elections: Fine-Grained Complexity.
Favorite-Candidate Voting for Eliminating the Least Popular Candidate in a Metric Space.
Private Bayesian Persuasion with Sequential Games.
Election Control in Social Networks via Edge Addition or Removal.
Persuading Voters: It's Easy to Whisper, It's Hard to Speak Loud.
Refining Tournament Solutions via Margin of Victory.
Approval-Based Apportionment.
Electing Successive Committees: Complexity and Algorithms.
Parameterized Algorithms for Finding a Collective Set of Items.
Adapting Stable Matchings to Evolving Preferences.
Individual-Based Stability in Hedonic Diversity Games.
Fair Division of Mixed Divisible and Indivisible Goods.
Facility Location Problem with Capacity Constraints: Algorithmic and Mechanism Design Perspectives.
All-Pay Bidding Games on Graphs.
Multiple Birds with One Stone: Beating 1/2 for EFX and GMMS via Envy Cycle Elimination.
Peeking Behind the Ordinal Curtain: Improving Distortion via Cardinal Queries.
Multiagent Evaluation Mechanisms.
The Impact of Selfishness in Hypergraph Hedonic Games.
Swap Stability in Schelling Games on Graphs.
Distance-Based Equilibria in Normal-Form Games.
Draft and Edit: Automatic Storytelling Through Multi-Pass Hierarchical Conditional Variational Autoencoder.
Fast and Robust Face-to-Parameter Translation for Game Character Auto-Creation.
A Character-Centric Neural Model for Automated Story Generation.
FET-GAN: Font and Effect Transfer via K-shot Adaptive Instance Normalization.
Narrative Planning Model Acquisition from Text Summaries and Descriptions.
Deep Reinforcement Learning for General Game Playing.
Generating Interactive Worlds with Text.
Deep Neural Network Approximated Dynamic Programming for Combinatorial Optimization.
Explaining Propagators for String Edit Distance Constraints.
Constructing Minimal Perfect Hash Functions Using SAT Technology.
Multiple Graph Matching and Clustering via Decayed Pairwise Matching Composition.
Hard Examples for Common Variable Decision Heuristics.
Probabilistic Inference for Predicate Constraint Satisfaction.
Efficient Algorithms for Generating Provably Near-Optimal Cluster Descriptors for Explainability.
Estimating the Density of States of Boolean Satisfiability Problems on Classical and Quantum Computing Platforms.
D-SPIDER-SFO: A Decentralized Optimization Algorithm with Faster Convergence Rate for Nonconvex Problems.
Grammar Filtering for Syntax-Guided Synthesis.
Smart Predict-and-Optimize for Hard Combinatorial Optimization Problems.
Accelerating Column Generation via Flexible Dual Optimal Inequalities with Application to Entity Resolution.
An Effective Hard Thresholding Method Based on Stochastic Variance Reduction for Nonconvex Sparse Learning.
Finding Good Subtrees for Constraint Optimization Problems Using Frequent Pattern Mining.
Solving Set Cover and Dominating Set via Maximum Satisfiability.
Augmenting the Power of (Partial) MaxSat Resolution with Extension.
FourierSAT: A Fourier Expansion-Based Algebraic Framework for Solving Hybrid Boolean Constraints.
Finding Most Compatible Phylogenetic Trees over Multi-State Characters.
Incremental Symmetry Breaking Constraints for Graph Search Problems.
Modelling Diversity of Solutions.
SPAN: A Stochastic Projected Approximate Newton Method.
Using Approximation within Constraint Programming to Solve the Parallel Machine Scheduling Problem with Additional Unit Resources.
MIPaaL: Mixed Integer Program as a Layer.
A Cardinal Improvement to Pseudo-Boolean Solving.
Justifying All Differences Using Pseudo-Boolean Reasoning.
Modelling and Solving Online Optimisation Problems.
ADDMC: Weighted Model Counting with Algebraic Decision Diagrams.
Optimization of Chance-Constrained Submodular Functions.
Accelerating Primal Solution Findings for Mixed Integer Programs Based on Solution Prediction.
Dynamic Programming for Predict+Optimise.
Representative Solutions for Bi-Objective Optimisation.
Guiding CDCL SAT Search via Random Exploration amid Conflict Depression.
Chain Length and CSPs Learnable with Few Queries.
Improved Filtering for the Euclidean Traveling Salesperson Problem in CLP(FD).
Deep Unsupervised Binary Coding Networks for Multivariate Time Series Retrieval.
Tensorized LSTM with Adaptive Shared Memory for Learning Trends in Multivariate Time Series.
Modeling Electrical Motor Dynamics Using Encoder-Decoder with Recurrent Skip Connection.
End-to-End Game-Focused Learning of Adversary Behavior in Security Games.
To Signal or Not To Signal: Exploiting Uncertain Real-Time Information in Signaling Games for Security and Sustainability.
M3ER: Multiplicative Multimodal Emotion Recognition using Facial, Textual, and Speech Cues.
Synch-Graph: Multisensory Emotion Recognition Through Neural Synchrony via Graph Convolutional Networks.
STEP: Spatial Temporal Graph Convolutional Networks for Emotion Perception from Gaits.
Machine Number Sense: A Dataset of Visual Arithmetic Problems for Abstract and Relational Reasoning.
Transfer Reinforcement Learning Using Output-Gated Working Memory.
Biologically Plausible Sequence Learning with Spiking Neural Networks.
Effective AER Object Classification Using Segmented Probability-Maximization Learning in Spiking Neural Networks.
People Do Not Just Plan, They Plan to Plan.
Deep Spiking Delayed Feedback Reservoirs and Its Application in Spectrum Sensing of MIMO-OFDM Dynamic Spectrum Sharing.
Theory-Based Causal Transfer: Integrating Instance-Level Induction and Abstract-Level Structure Learning.
MixedAD: A Scalable Algorithm for Detecting Mixed Anomalies in Attributed Graphs.
Deep Reservoir Computing Meets 5G MIMO-OFDM Systems in Symbol Detection.
RiskOracle: A Minute-Level Citywide Traffic Accident Forecasting Framework.
Iteratively Questioning and Answering for Interpretable Legal Judgment Prediction.
Index Tracking with Cardinality Constraints: A Stochastic Neural Networks Approach.
GMAN: A Graph Multi-Attention Network for Traffic Prediction.
MaskGEC: Improving Neural Grammatical Error Correction via Dynamic Masking.
OF-MSRN: Optical Flow-Auxiliary Multi-Task Regression Network for Direct Quantitative Measurement, Segmentation and Motion Estimation.
Dynamic Malware Analysis with Feature Engineering and Feature Learning.
A Novel Learning Framework for Sampling-Based Motion Planning in Autonomous Driving.
Shoreline: Data-Driven Threshold Estimation of Online Reserves of Cryptocurrency Trading Platforms.
Semi-Supervised Hierarchical Recurrent Graph Neural Network for City-Wide Parking Availability Prediction.
Spatio-Temporal Graph Structure Learning for Traffic Forecasting.
Generating Adversarial Examples for Holding Robustness of Source Code Processing Models.
Geometry-Constrained Car Recognition Using a 3D Perspective Network.
MetaLight: Value-Based Meta-Reinforcement Learning for Traffic Signal Control.
Order Matters: Semantic-Aware Neural Networks for Binary Code Similarity Detection.
Towards Hands-Free Visual Dialog Interactive Recommendation.
AirNet: A Calibration Model for Low-Cost Air Monitoring Sensors Using Dual Sequence Encoder Networks.
Attention Based Data Hiding with Generative Adversarial Networks.
Reinforcement-Learning Based Portfolio Management with Augmented Asset Movement Prediction States.
Instance-Wise Dynamic Sensor Selection for Human Activity Recognition.
Scalable and Generalizable Social Bot Detection through Data Selection.
Beyond Digital Domain: Fooling Deep Learning Based Recognition System in Physical World.
Fairness-Aware Demand Prediction for New Mobility.
Generate (Non-Software) Bugs to Fool Classifiers.
Generative Adversarial Regularized Mutual Information Policy Gradient Framework for Automatic Diagnosis.
Graph Convolutional Networks with Markov Random Field Reasoning for Social Spammer Detection.
Accelerating and Improving AlphaZero Using Population Based Training.
DeepDualMapper: A Gated Fusion Network for Automatic Map Extraction Using Aerial Images and Trajectories.
A Deep Neural Network Model of Particle Thermal Radiation in Packed Bed.
Hiding in Multilayer Networks.
Urban2Vec: Incorporating Street View Imagery and POIs for Multi-Modal Urban Neighborhood Embedding.
Actor Critic Deep Reinforcement Learning for Neural Malware Control.
HDK: Toward High-Performance Deep-Learning-Based Kirchhoff Analysis.
Topic Enhanced Sentiment Spreading Model in Social Networks Considering User Interest.
Graph-Driven Generative Models for Heterogeneous Multi-Task Learning.
Incorporating Expert-Based Investment Opinion Signals in Stock Prediction: A Deep Learning Framework.
OMuLeT: Online Multi-Lead Time Location Prediction for Hurricane Trajectory Forecasting.
Robust Adversarial Objects against Deep Learning Models.
Finding Needles in a Moving Haystack: Prioritizing Alerts with Adversarial Reinforcement Learning.
Finding Minimum-Weight Link-Disjoint Paths with a Few Common Nodes.
DATA-GRU: Dual-Attention Time-Aware Gated Recurrent Unit for Irregular Multivariate Time Series.
Continuous Multiagent Control Using Collective Behavior Entropy for Large-Scale Home Energy Management.
Spatial-Temporal Synchronous Graph Convolutional Networks: A New Framework for Spatial-Temporal Network Data Forecasting.
Effective Decoding in Graph Auto-Encoder Using Triadic Closure.
Spatial Classification with Limited Observations Based on Physics-Aware Structural Constraint.
Learning to Generate Maps from Trajectories.
FuzzE: Fuzzy Fairness Evaluation of Offensive Language Classifiers on African-American English.
Chemically Interpretable Graph Interaction Network for Prediction of Pharmacokinetic Properties of Drug-Like Molecules.
ActiveThief: Model Extraction Using Active Learning and Unannotated Public Data.
Generalizable Resource Allocation in Stream Processing via Deep Reinforcement Learning.
Gait Recognition for Co-Existing Multiple People Using Millimeter Wave Sensing.
Bursting the Filter Bubble: Fairness-Aware Network Link Prediction.
ConCare: Personalized Clinical Feature Embedding via Capturing the Healthcare Context.
AdaCare: Explainable Clinical Health Status Representation Learning via Scale-Adaptive Feature Extraction and Recalibration.
Learning Multi-Modal Biomarker Representations via Globally Aligned Longitudinal Enrichments.
Learning Geo-Contextual Embeddings for Commuting Flow Prediction.
PSENet: Psoriasis Severity Evaluation Network.
MRI Reconstruction with Interpretable Pixel-Wise Operations Using Reinforcement Learning.
Privacy-Preserving Gradient Boosting Decision Trees.
Towards Cross-Modality Medical Image Segmentation with Online Mutual Knowledge Distillation.
Robust Low-Rank Discovery of Data-Driven Partial Differential Equations.
Pose-Assisted Multi-Camera Collaboration for Active Object Tracking.
Region Focus Network for Joint Optic Disc and Cup Segmentation.
DeepAlerts: Deep Learning Based Multi-Horizon Alerts for Clinical Deterioration on Oncology Hospital Wards.
SynSig2Vec: Learning Representations from Synthetic Dynamic Signatures for Real-World Verification.
Generating Realistic Stock Market Order Streams.
A Graph Auto-Encoder for Haplotype Assembly and Viral Quasispecies Reconstruction.
RL-Duet: Online Music Accompaniment Generation Using Deep Reinforcement Learning.
CASTER: Predicting Drug Interactions with Chemical Substructure Representation.
Pairwise Learning with Differential Privacy Guarantees.
Accurate Structured-Text Spotting for Arithmetical Exercise Correction.
Multi-Scale Anomaly Detection on Attributed Networks.
Graduate Employment Prediction with Bias.
Enhancing Personalized Trip Recommendation with Attractive Routes.
Predictive Student Modeling in Educational Games with Multi-Task Learning.
GAN-Based Unpaired Chinese Character Image Translation via Skeleton Transformation and Stroke Rendering.
CORE: Automatic Molecule Optimization Using Copy & Refine Strategy.
Predicting AC Optimal Power Flows: Combining Deep Learning and Lagrangian Dual Methods.
Differentially Private and Fair Classification via Calibrated Functional Mechanism.
CONAN: Complementary Pattern Augmentation for Rare Disease Detection.
Learning the Graphical Structure of Electronic Health Records with Graph Convolutional Transformer.
DeepVar: An End-to-End Deep Learning Approach for Genomic Variant Recognition in Biomedical Literature.
Adaptive Greedy versus Non-Adaptive Greedy for Influence Maximization.
Pay Your Trip for Traffic Congestion: Dynamic Pricing in Traffic-Aware Road Networks.
Real-Time Route Search by Locations.
TrueLearn: A Family of Bayesian Algorithms to Match Lifelong Learners to Open Educational Resources.
Doctor2Vec: Dynamic Doctor Representation Learning for Clinical Trial Recruitment.
Rumor Detection on Social Media with Bi-Directional Graph Convolutional Networks.
Interactive Learning with Proactive Cognition Enhancement for Crowd Workers.
Weakly-Supervised Fine-Grained Event Recognition on Social Media Texts for Disaster Management.
Protecting Geolocation Privacy of Photo Collections.
Weak Supervision for Fake News Detection via Reinforcement Learning.
Neural Approximate Dynamic Programming for On-Demand Ride-Pooling.
On Identifying Hashtags in Disaster Twitter Data.
Capturing the Style of Fake News.
Automatically Neutralizing Subjective Bias in Text.
The Stanford Acuity Test: A Precise Vision Test Using Bayesian Techniques and a Discovery in Human Visual Response.
Guided Weak Supervision for Action Recognition with Scarce Data to Assess Skills of Children with Autism.
Voice for the Voiceless: Active Sampling to Detect Comments Supporting the Rohingyas.
Linguistic Fingerprints of Internet Censorship: The Case of Sina Weibo.
The Unreasonable Effectiveness of Inverse Reinforcement Learning in Advancing Cancer Research.
Lightweight and Robust Representation of Economic Scales from Satellite Imagery.
Discriminating Cognitive Disequilibrium and Flow in Problem Solving: A Semi-Supervised Approach Using Involuntary Dynamic Behavioral Signals.
Faking Fairness via Stealthily Biased Sampling.
A Distributed Multi-Sensor Machine Learning Approach to Earthquake Early Warning.
Inferring Nighttime Satellite Imagery from Human Mobility.
Hindi-English Hate Speech Detection: Author Profiling, Debiasing, and Practical Perspectives.
Detecting and Tracking Communal Bird Roosts in Weather Radar Data.
Tracking Disaster Footprints with Social Streaming Data.
Spatio-Temporal Attention-Based Neural Network for Credit Card Fraud Detection.
Unsupervised Detection of Sub-Events in Large Scale Disasters.
Crisis-DIAS: Towards Multimodal Damage Analysis - Deployment, Challenges and Assessment.
FairyTED: A Fair Rating Predictor for TED Talk Data.
A Recurrent Model for Collective Entity Linking with Adaptive Features.
Table2Analysis: Modeling and Recommendation of Common Analysis Patterns for Multi-Dimensional Data.
Multi-Channel Reverse Dictionary Model.
An End-to-End Visual-Audio Attention Network for Emotion Recognition in User-Generated Videos.
D2D-LSTM: LSTM-Based Path Prediction of Content Diffusion Tree in Device-to-Device Social Networks.
Learning to Match on Graph for Fashion Compatibility Modeling.
Cross-Modal Attention Network for Temporal Inconsistent Audio-Visual Event Localization.
Multi-Feature Discrete Collaborative Filtering for Fast Cold-Start Recommendation.
Who Likes What? - SplitLBI in Exploring Preferential Diversity of Ratings.
Mining Unfollow Behavior in Large-Scale Online Social Networks via Spatial-Temporal Interaction.
Social Influence Does Matter: User Action Prediction for In-Feed Advertising.
Author Name Disambiguation on Heterogeneous Information Network with Adversarial Representation Learning.
Learning with Unsure Responses.
Knowledge Graph Alignment Network with Gated Multi-Hop Neighborhood Aggregation.
Where to Go Next: Modeling Long- and Short-Term User Preferences for Point-of-Interest Recommendation.
PEIA: Personality and Emotion Integrated Attentive Model for Music Recommendation on Social Media Platforms.
Minimizing the Bag-of-Ngrams Difference for Non-Autoregressive Neural Machine Translation.
Towards Comprehensive Recommender Systems: Time-Aware Unified Recommendations Based on Listwise Ranking of Implicit Cross-Network Data.
Fair Updates in Two-Sided Market Platforms: On Incrementally Updating Recommendations.
A Variational Point Process Model for Social Event Sequences.
Modality to Modality Translation: An Adversarial Representation Learning and Graph Fusion Network for Multimodal Fusion.
Deep Match to Rank Model for Personalized Click-Through Rate Prediction.
Type-Aware Anchor Link Prediction across Heterogeneous Networks Based on Graph Attention Network.
Understanding and Improving Proximity Graph Based Maximum Inner Product Search.
True Nonlinear Dynamics from Incomplete Networks.
Functionality Discovery and Prediction of Physical Objects.
Cross-Lingual Pre-Training Based Transfer for Zero-Shot Neural Machine Translation.
MuMod: A Micro-Unit Connection Approach for Hybrid-Order Community Detection.
Semi-Supervised Multi-Modal Learning with Balanced Spectral Decomposition.
Re-Attention for Visual Question Answering.
An Attentional Recurrent Neural Network for Personalized Next Location Recommendation.
Preserving Ordinal Consensus: Towards Feature Selection for Unlabeled Data.
Leveraging Title-Abstract Attentive Semantics for Paper Recommendation.
Modeling Fluency and Faithfulness for Diverse Neural Machine Translation.
Norm-Explicit Quantization: Improving Vector Quantization for Maximum Inner Product Search.
Gradient Method for Continuous Influence Maximization with Budget-Saving Considerations.
Question-Driven Purchasing Propensity Analysis for Recommendation.
Revisiting Graph Based Collaborative Filtering: A Linear Residual Graph Convolutional Network Approach.
Efficient Heterogeneous Collaborative Filtering without Negative Sampling for Recommendation.
MultiSumm: Towards a Unified Model for Multi-Lingual Abstractive Summarization.
Balancing Spreads of Influence in a Social Network.
