ijcai 2020 论文列表
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, IJCAI 2020.
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AI-Powered Oracle Bone Inscriptions Recognition and Fragments Rejoining.
Towards Real-Time DNN Inference on Mobile Platforms with Model Pruning and Compiler Optimization.
A Speech-to-Knowledge-Graph Construction System.
SiamBOMB: A Real-time AI-based System for Home-cage Animal Tracking, Segmentation and Behavioral Analysis.
A Gamified Assessment Platform for Predicting the Risk of Dementia +Parkinson's disease (DPD) Co-Morbidity.
A Testbed for Studying COVID-19 Spreading in Ride-Sharing Systems.
Lossless Semantic Round-Tripping in PENG ASP.
Decision Platform for Pattern Discovery and Causal Effect Estimation in Contraceptive Discontinuation.
ProbAnch: a Modular Probabilistic Anchoring Framework.
Inspection of Blackbox Models for Evaluating Vulnerability in Maternal, Newborn, and Child Health.
A Multi-player Game for Studying Federated Learning Incentive Schemes.
Putting Accountability of AI Systems into Practice.
FlowSynth: Simplifying Complex Audio Generation Through Explorable Latent Spaces with Normalizing Flows.
Keep It Real: a Window to Real Reality in Virtual Reality.
An AI-empowered Visual Storyline Generator.
RLCard: A Platform for Reinforcement Learning in Card Games.
An Interactive Visualization Platform for Deep Symbolic Regression.
AILA: A Question Answering System in the Legal Domain.
AutoSurvey: Automatic Survey Generation based on a Research Draft.
BlueMemo: Depression Analysis through Twitter Posts.
Certifai: A Toolkit for Building Trust in AI Systems.
How Causal Structural Knowledge Adds Decision-Support in Monitoring of Automotive Body Shop Assembly Lines.
Ddo, a Generic and Efficient Framework for MDD-Based Optimization.
TouIST: a Friendly Language for Propositional Logic and More.
Efficient and Modularized Training on FPGA for Real-time Applications.
Yolo4Apnea: Real-time Detection of Obstructive Sleep Apnea.
DeepVentilation: Learning to Predict Physical Effort from Breathing.
An Anomaly Detection and Explainability Framework using Convolutional Autoencoders for Data Storage Systems.
Pattern-Based Music Generation with Wasserstein Autoencoders and PRC Descriptions.
PyDL8.5: a Library for Learning Optimal Decision Trees.
GenC: A Fast Tool for Applications Involving Belief Revision.
Generalized Representation Learning Methods for Deep Reinforcement Learning.
Beyond Labels: Knowledge Elicitation using Deep Metric Learning and Psychometric Testing.
End-to-End Signal Factorization for Speech: Identity, Content, and Style.
Predictive Uncertainty Estimation for Tractable Deep Probabilistic Models.
Context Aware Sequence Modeling.
Towards an Artificial Argumentation System.
Generating Natural Counterfactual Visual Explanations.
Spatio-Temporal Change Detection Using Granger Sequence Pattern.
On Building an Interpretable Topic Modeling Approach for the Urdu Language.
Social Network Analysis using RLVECN: Representation Learning via Knowledge-Graph Embeddings and Convolutional Neural-Network.
Strategies for Cooperative UAVs Using Model Predictive Control.
Design Adaptive AI for RTS Game by Learning Player's Build Order.
Population Location and Movement Estimation through Cross-domain Data Analysis.
Learning Sparse Neural Networks for Better Generalization.
An Improved Latent Low Rank Representation for Automatic Subspace Clustering.
Towards High-Level Intrinsic Exploration in Reinforcement Learning.
Transparent Intent for Explainable Shared Control in Assistive Robotics.
Online Learning in Changing Environments.
Mechanism Design with Uncertainty.
Closing the Loop: Bringing Humans into Empirical Computational Social Choice and Preference Reasoning.
Optimization Learning: Perspective, Method, and Applications.
Developing an Integrated Model of Speech Entrainment.
Towards Trustable Explainable AI.
Bridging Causality and Learning: How Do They Benefit from Each Other?
IKBT: Solving Symbolic Inverse Kinematics with Behavior Tree (Extended Abstract).
Incentivizing Evaluation with Peer Prediction and Limited Access to Ground Truth (Extended Abstract).
OptStream: Releasing Time Series Privately (Extended Abstract).
Best-first Enumeration Based on Bounding Conflicts, and its Application to Large-scale Hybrid Estimation (Extended Abstract).
Swarm Intelligence for Self-Organized Clustering (Extended Abstract).
Knowing-How under Uncertainty (Extended Abstract).
Context Vectors Are Reflections of Word Vectors in Half the Dimensions (Extended Abstract).
Language Independent Sequence Labelling for Opinion Target Extraction (Extended Abstract).
The Computational Complexity of Angry Birds (Extended Abstract).
From Support Propagation to Belief Propagation in Constraint Programming (Extended Abstract).
Catching Cheats: Detecting Strategic Manipulation in Distributed Optimisation of Electric Vehicle Aggregators (Extended Abstract).
Formulas Free From Inconsistency: An Atom-Centric Characterization in Priest's Minimally Inconsistent LP (Extended Abstract).
A Survey on Temporal Reasoning for Temporal Information Extraction from Text (Extended Abstract).
Point at the Triple: Generation of Text Summaries from Knowledge Base Triples (Extended Abstract).
Proving Semantic Properties as First-Order Satisfiability (Extended Abstract).
Story Embedding: Learning Distributed Representations of Stories based on Character Networks (Extended Abstract).
Compositionality Decomposed: How do Neural Networks Generalise? (Extended Abstract).
Ontology Reasoning with Deep Neural Networks (Extended Abstract).
On Overfitting and Asymptotic Bias in Batch Reinforcement Learning with Partial Observability (Extended Abstract).
Variational Bayes in Private Settings (VIPS) (Extended Abstract).
Algorithms for Estimating the Partition Function of Restricted Boltzmann Machines (Extended Abstract).
Determining Inference Semantics for Disjunctive Logic Programs (Extended Abstract).
Variable Elimination in Binary CSPs (Extended Abstract).
Automated Construction of Bounded-Loss Imperfect-Recall Abstractions in Extensive-Form Games (Extended Abstract).
Rational Closure For All Description Logics (Extended Abstract).
Predicting Strategic Behavior from Free Text (Extended Abstract).
Analogy Between Concepts (Extended Abstract).
Xeggora: Exploiting Immune-to-Evidence Symmetries with Full Aggregation in Statistical Relational Models (Extended Abstract).
Forgetting Auxiliary Atoms in Forks (Extended Abstract).
A Survey on Representation Learning for User Modeling.
Learning for Graph Matching and Related Combinatorial Optimization Problems.
Deep Learning for Community Detection: Progress, Challenges and Opportunities.
Beyond Intra-modality: A Survey of Heterogeneous Person Re-identification.
Fair Division: The Computer Scientist's Perspective.
Pure-Past Linear Temporal and Dynamic Logic on Finite Traces.
Human Gaze Assisted Artificial Intelligence: A Review.
From Statistical Relational to Neuro-Symbolic Artificial Intelligence.
The Knowledge Acquisition Bottleneck Problem in Multilingual Word Sense Disambiguation.
Incorporating Extra Knowledge to Enhance Word Embedding.
Recent Developments in Boolean Matrix Factorization.
BDI Agent Architectures: A Survey.
A Survey on Using Gaze Behaviour for Natural Language Processing.
Reasoning About Inconsistent Formulas.
Planning Algorithms for Zero-Sum Games with Exponential Action Spaces: A Unifying Perspective.
Collective Decision Making under Incomplete Knowledge: Possible and Necessary Solutions.
Graph Neural Networks Meet Neural-Symbolic Computing: A Survey and Perspective.
A Brief History of Learning Symbolic Higher-Level Representations from Data (And a Curious Look Forward).
Heterogeneous Network Representation Learning.
From Standard Summarization to New Tasks and Beyond: Summarization with Manifold Information.
Goal Recognition Design - Survey.
The Blind Men and the Elephant: Integrated Offline/Online Optimization Under Uncertainty.
Turning 30: New Ideas in Inductive Logic Programming.
A Survey on Computational Propaganda Detection.
Automatic Curriculum Learning For Deep RL: A Short Survey.
Explanation Perspectives from the Cognitive Sciences - A Survey.
The Emerging Landscape of Explainable Automated Planning & Decision Making.
Survey on Feature Transformation Techniques for Data Streams.
Bridging the Gap between Training and Inference for Neural Machine Translation (Extended Abstract).
A User Interface for Exploring and Querying Knowledge Graphs (Extended Abstract).
Deep Visuo-Tactile Learning: Estimation of Tactile Properties from Images (Extended Abstract).
Bidirectional Heuristic Search: Expanding Nodes by a Lower Bound.
Lagrangian Decomposition for Classical Planning (Extended Abstract).
Learning Optimal Decision Trees using Constraint Programming (Extended Abstract).
Commonsense Reasoning to Guide Deep Learning for Scene Understanding (Extended Abstract).
Supporting Historical Photo Identification with Face Recognition and Crowdsourced Human Expertise (Extended Abstract).
NSGA-Net: Neural Architecture Search using Multi-Objective Genetic Algorithm (Extended Abstract).
Specializing Word Embeddings (for Parsing) by Information Bottleneck (Extended Abstract).
Bayesian Case-Exclusion and Personalized Explanations for Sustainable Dairy Farming (Extended Abstract).
Human Values and Digital Patterns in Physical Exercise (Extended Abstract).
Learning URI Selection Criteria to Improve the Crawling of Linked Open Data (Extended Abstract).
Statistical Learning with a Nuisance Component (Extended Abstract).
On the Splitting Property for Epistemic Logic Programs (Extended Abstract).
A Formal Approach for Cautious Reasoning in Answer Set Programming (Extended Abstract).
Playing Atari with Six Neurons (Extended Abstract).
Methodological Issues in Recommender Systems Research (Extended Abstract).
Emoji-Powered Representation Learning for Cross-Lingual Sentiment Classification (Extended Abstract).
VAEP: An Objective Approach to Valuing On-the-Ball Actions in Soccer (Extended Abstract).
Hierarchical Reinforcement Learning for Pedagogical Policy Induction (Extended Abstract).
Online Portfolio Selection with Cardinality Constraint and Transaction Costs based on Contextual Bandit.
Interpretable Multimodal Learning for Intelligent Regulation in Online Payment Systems.
A Unified Model for Financial Event Classification, Detection and Summarization.
Financial Risk Analysis for SMEs with Graph-based Supply Chain Mining.
Federated Meta-Learning for Fraudulent Credit Card Detection.
Relation-Aware Transformer for Portfolio Policy Learning.
Hierarchical Multi-Scale Gaussian Transformer for Stock Movement Prediction.
Two-stage Behavior Cloning for Spoken Dialogue System in Debt Collection.
Market Manipulation: An Adversarial Learning Framework for Detection and Evasion.
Financial Thought Experiment: A GAN-based Approach to Vast Robust Portfolio Selection.
The Behavioral Sign of Account Theft: Realizing Online Payment Fraud Alert.
Infochain: A Decentralized, Trustless and Transparent Oracle on Blockchain.
"The Squawk Bot": Joint Learning of Time Series and Text Data Modalities for Automated Financial Information Filtering.
Robust Market Making via Adversarial Reinforcement Learning.
Risk-Averse Trust Region Optimization for Reward-Volatility Reduction.
Financial Risk Prediction with Multi-Round Q&A Attention Network.
RM-CVaR: Regularized Multiple β-CVaR Portfolio.
Multi-scale Two-way Deep Neural Network for Stock Trend Prediction.
An End-to-End Optimal Trade Execution Framework based on Proximal Policy Optimization.
Modeling the Stock Relation with Graph Network for Overnight Stock Movement Prediction.
IGNITE: A Minimax Game Toward Learning Individual Treatment Effects from Networked Observational Data.
A Two-level Reinforcement Learning Algorithm for Ambiguous Mean-variance Portfolio Selection Problem.
MAPS: Multi-Agent reinforcement learning-based Portfolio management System.
FinBERT: A Pre-trained Financial Language Representation Model for Financial Text Mining.
Phishing Scam Detection on Ethereum: Towards Financial Security for Blockchain Ecosystem.
SEBF: A Single-Chain based Extension Model of Blockchain for Fintech.
F-HMTC: Detecting Financial Events for Investment Decisions Based on Neural Hierarchical Multi-Label Text Classification.
Risk Guarantee Prediction in Networked-Loans.
Task-Based Learning via Task-Oriented Prediction Network with Applications in Finance.
Vector Autoregressive Weighting Reversion Strategy for Online Portfolio Selection.
Data-Driven Market-Making via Model-Free Learning.
A Quantum-inspired Entropic Kernel for Multiple Financial Time Series Analysis.
Deep Semantic Compliance Advisor for Unstructured Document Compliance Checking.
BitcoinHeist: Topological Data Analysis for Ransomware Prediction on the Bitcoin Blockchain.
Multi-View Joint Graph Representation Learning for Urban Region Embedding.
PewLSTM: Periodic LSTM with Weather-Aware Gating Mechanism for Parking Behavior Prediction.
Real-Time Dispatching of Large-Scale Ride-Sharing Systems: Integrating Optimization, Machine Learning, and Model Predictive Control.
Generating Interpretable Poverty Maps using Object Detection in Satellite Images.
Discrete Biorthogonal Wavelet Transform Based Convolutional Neural Network for Atrial Fibrillation Diagnosis from Electrocardiogram.
Who Am I?: Towards Social Self-Awareness for Intelligent Agents.
Optimal and Non-Discriminative Rehabilitation Program Design for Opioid Addiction Among Homeless Youth.
Forecasting Avian Migration Patterns using a Deep Bidirectional RNN Augmented with an Auxiliary Task.
Deep Hurdle Networks for Zero-Inflated Multi-Target Regression: Application to Multiple Species Abundance Estimation.
Harnessing Code Switching to Transcend the Linguistic Barrier.
Cross-Interaction Hierarchical Attention Networks for Urban Anomaly Prediction.
An Exact Single-Agent Task Selection Algorithm for the Crowdsourced Logistics.
Improving Tandem Mass Spectra Analysis with Hierarchical Learning.
Embedding Conjugate Gradient in Learning Random Walks for Landscape Connectivity Modeling in Conservation.
Bridging Cross-Tasks Gap for Cognitive Assessment via Fine-Grained Domain Adaptation.
Fighting Wildfires under Uncertainty - A Sequential Resource Allocation Approach.
Disentangled Variational Autoencoder based Multi-Label Classification with Covariance-Aware Multivariate Probit Model.
Adversarial Graph Embeddings for Fair Influence Maximization over Social Networks.
A Novel Spatio-Temporal Multi-Task Approach for the Prediction of Diabetes-Related Complication: a Cardiopathy Case of Study.
State Variable Effects in Graphical Event Models.
A Complete Characterization of Projectivity for Statistical Relational Models.
Neural Belief Reasoner.
Scaling Up AND/OR Abstraction Sampling.
Efficient and Robust High-Dimensional Linear Contextual Bandits.
Approximate Weighted First-Order Model Counting: Exploiting Fast Approximate Model Counters and Symmetry.
Learning Bayesian Networks Under Sparsity Constraints: A Parameterized Complexity Analysis.
Lifted Hybrid Variational Inference.
Euclidean Pathfinding with Compressed Path Databases.
Crowd-Steer: Realtime Smooth and Collision-Free Robot Navigation in Densely Crowded Scenarios Trained using High-Fidelity Simulation.
Multi-Robot Adversarial Patrolling Strategies via Lattice Paths.
A Unified Model for the Two-stage Offline-then-Online Resource Allocation.
Trade the System Efficiency for the Income Equality of Drivers in Rideshare.
DualSMC: Tunneling Differentiable Filtering and Planning under Continuous POMDPs.
Boundary Extension Features for Width-Based Planning with Simulators on Continuous-State Domains.
Trading Plan Cost for Timeliness in Situated Temporal Planning.
Robustness Computation of Dynamic Controllability in Probabilistic Temporal Networks with Ordinary Distributions.
Decidability Results in First-Order Epistemic Planning.
Cost-Partitioned Merge-and-Shrink Heuristics for Optimal Classical Planning.
Optimising Partial-Order Plans Via Action Reinstantiation.
Sparse Tree Search Optimality Guarantees in POMDPs with Continuous Observation Spaces.
Optimal Planning Modulo Theories.
Verifiable RNN-Based Policies for POMDPs Under Temporal Logic Constraints.
Robust Policy Synthesis for Uncertain POMDPs via Convex Optimization.
Online Revenue Maximization for Server Pricing.
Front-to-Front Heuristic Search for Satisficing Classical Planning.
Plan-Space Explanation via Plan-Property Dependencies: Faster Algorithms & More Powerful Properties.
Iterative-Deepening Conflict-Based Search.
Delete- and Ordering-Relaxation Heuristics for HTN Planning.
Steady-State Policy Synthesis in Multichain Markov Decision Processes.
Multi-Directional Heuristic Search.
A Relation-Specific Attention Network for Joint Entity and Relation Extraction.
Fast and Accurate Neural CRF Constituency Parsing.
Knowledge Graphs Enhanced Neural Machine Translation.
Modeling Dense Cross-Modal Interactions for Joint Entity-Relation Extraction.
Gated POS-Level Language Model for Authorship Verification.
Generalized Zero-Shot Text Classification for ICD Coding.
Teacher-Student Networks with Multiple Decoders for Solving Math Word Problem.
TransOMCS: From Linguistic Graphs to Commonsense Knowledge.
ERNIE-GEN: An Enhanced Multi-Flow Pre-training and Fine-tuning Framework for Natural Language Generation.
Hype-HAN: Hyperbolic Hierarchical Attention Network for Semantic Embedding.
Towards Making the Most of Context in Neural Machine Translation.
Leveraging Document-Level Label Consistency for Named Entity Recognition.
Dataless Short Text Classification Based on Biterm Topic Model and Word Embeddings.
A Structured Latent Variable Recurrent Network With Stochastic Attention For Generating Weibo Comments.
Exploring Bilingual Parallel Corpora for Syntactically Controllable Paraphrase Generation.
Asking Effective and Diverse Questions: A Machine Reading Comprehension based Framework for Joint Entity-Relation Extraction.
Enhancing Dialog Coherence with Event Graph Grounded Content Planning.
Efficient Context-Aware Neural Machine Translation with Layer-Wise Weighting and Input-Aware Gating.
UniTrans : Unifying Model Transfer and Data Transfer for Cross-Lingual Named Entity Recognition with Unlabeled Data.
Better AMR-To-Text Generation with Graph Structure Reconstruction.
Gaussian Embedding of Linked Documents from a Pretrained Semantic Space.
Multi-hop Reading Comprehension across Documents with Path-based Graph Convolutional Network.
Alleviate Dataset Shift Problem in Fine-grained Entity Typing with Virtual Adversarial Training.
Neural Machine Translation with Error Correction.
Transformers as Soft Reasoners over Language.
Hierarchical Multi-task Learning for Organization Evaluation of Argumentative Student Essays.
End-to-End Transition-Based Online Dialogue Disentanglement.
Task-Level Curriculum Learning for Non-Autoregressive Neural Machine Translation.
CoSDA-ML: Multi-Lingual Code-Switching Data Augmentation for Zero-Shot Cross-Lingual NLP.
Dialogue State Induction Using Neural Latent Variable Models.
MuLaN: Multilingual Label propagatioN for Word Sense Disambiguation.
On the Importance of Word and Sentence Representation Learning in Implicit Discourse Relation Classification.
Answer Generation through Unified Memories over Multiple Passages.
Joint Time-Frequency and Time Domain Learning for Speech Enhancement.
Learning with Noise: Improving Distantly-Supervised Fine-grained Entity Typing via Automatic Relabeling.
Text Style Transfer via Learning Style Instance Supported Latent Space.
An Iterative Multi-Source Mutual Knowledge Transfer Framework for Machine Reading Comprehension.
Attention as Relation: Learning Supervised Multi-head Self-Attention for Relation Extraction.
Triple-to-Text Generation with an Anchor-to-Prototype Framework.
Infobox-to-text Generation with Tree-like Planning based Attention Network.
TopicKA: Generating Commonsense Knowledge-Aware Dialogue Responses Towards the Recommended Topic Fact.
Towards Fully 8-bit Integer Inference for the Transformer Model.
Formal Query Building with Query Structure Prediction for Complex Question Answering over Knowledge Base.
Robust Front-End for Multi-Channel ASR using Flow-Based Density Estimation.
Modeling Topical Relevance for Multi-Turn Dialogue Generation.
Evaluating Natural Language Generation via Unbalanced Optimal Transport.
Domain Adaptation for Semantic Parsing.
Neural Abstractive Summarization with Structural Attention.
A De Novo Divide-and-Merge Paradigm for Acoustic Model Optimization in Automatic Speech Recognition.
Unsupervised Multilingual Alignment using Wasserstein Barycenter.
Modeling Voting for System Combination in Machine Translation.
Generating Reasonable Legal Text through the Combination of Language Modeling and Question Answering.
Retrieve, Program, Repeat: Complex Knowledge Base Question Answering via Alternate Meta-learning.
Unsupervised Domain Adaptation of a Pretrained Cross-Lingual Language Model.
Hierarchical Matching Network for Heterogeneous Entity Resolution.
Global Structure and Local Semantics-Preserved Embeddings for Entity Alignment.
Learning Latent Forests for Medical Relation Extraction.
RECPARSER: A Recursive Semantic Parsing Framework for Text-to-SQL Task.
EmoElicitor: An Open Domain Response Generation Model with User Emotional Reaction Awareness.
Guided Generation of Cause and Effect.
LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning.
Two-Phase Hypergraph Based Reasoning with Dynamic Relations for Multi-Hop KBQA.
Knowledge Enhanced Event Causality Identification with Mention Masking Generalizations.
Exemplar Guided Neural Dialogue Generation.
Attention-based Multi-level Feature Fusion for Named Entity Recognition.
Lexical-Constraint-Aware Neural Machine Translation via Data Augmentation.
How Far are We from Effective Context Modeling? An Exploratory Study on Semantic Parsing in Context.
Hierarchical Linear Disentanglement of Data-Driven Conceptual Spaces.
CooBa: Cross-project Bug Localization via Adversarial Transfer Learning.
Pivot-based Maximal Biclique Enumeration.
An Interactive Multi-Task Learning Framework for Next POI Recommendation with Uncertain Check-ins.
Efficient Community Search over Large Directed Graph: An Augmented Index-based Approach.
Learning the Compositional Visual Coherence for Complementary Recommendations.
Learning Model with Error - Exposing the Hidden Model of BAYHENN.
An Attention-based Model for Conversion Rate Prediction with Delayed Feedback via Post-click Calibration.
Community-Centric Graph Convolutional Network for Unsupervised Community Detection.
Auxiliary Template-Enhanced Generative Compatibility Modeling.
BERT-PLI: Modeling Paragraph-Level Interactions for Legal Case Retrieval.
Modeling Perception Errors towards Robust Decision Making in Autonomous Vehicles.
HyperNews: Simultaneous News Recommendation and Active-Time Prediction via a Double-Task Deep Neural Network.
Differential Privacy for Stackelberg Games.
A Game Theoretic Approach For Core Resilience.
MLS3RDUH: Deep Unsupervised Hashing via Manifold based Local Semantic Similarity Structure Reconstructing.
Why We Go Where We Go: Profiling User Decisions on Choosing POIs.
Learning Data-Driven Drug-Target-Disease Interaction via Neural Tensor Network.
FakeSpotter: A Simple yet Robust Baseline for Spotting AI-Synthesized Fake Faces.
Learning to Accelerate Heuristic Searching for Large-Scale Maximum Weighted b-Matching Problems in Online Advertising.
A Two-Stage Matheuristic Algorithm for Classical Inventory Routing Problem.
Optimal Policy for Deployment of Machine Learning Models on Energy-Bounded Systems.
Exploiting Mutual Information for Substructure-aware Graph Representation Learning.
Automatic Emergency Diagnosis with Knowledge-Based Tree Decoding.
Towards Alleviating Traffic Congestion: Optimal Route Planning for Massive-Scale Trips.
The Graph-based Mutual Attentive Network for Automatic Diagnosis.
HID: Hierarchical Multiscale Representation Learning for Information Diffusion.
CDC: Classification Driven Compression for Bandwidth Efficient Edge-Cloud Collaborative Deep Learning.
Generating Behavior-Diverse Game AIs with Evolutionary Multi-Objective Deep Reinforcement Learning.
C3MM: Clique-Closure based Hyperlink Prediction.
Inverse Reinforcement Learning for Team Sports: Valuing Actions and Players.
Semi-Markov Reinforcement Learning for Stochastic Resource Collection.
Predicting Landslides Using Locally Aligned Convolutional Neural Networks.
A Label Attention Model for ICD Coding from Clinical Text.
Binary Classification from Positive Data with Skewed Confidence.
Adversarial Mutual Information Learning for Network Embedding.
DeepWeave: Accelerating Job Completion Time with Deep Reinforcement Learning-based Coflow Scheduling.
Inferring Degrees from Incomplete Networks and Nonlinear Dynamics.
Neighbor Combinatorial Attention for Critical Structure Mining.
Unsupervised Domain Adaptation with Dual-Scheme Fusion Network for Medical Image Segmentation.
Smart Contract Vulnerability Detection using Graph Neural Network.
Tight Convergence Rate of Gradient Descent for Eigenvalue Computation.
Closing the Generalization Gap of Adaptive Gradient Methods in Training Deep Neural Networks.
pbSGD: Powered Stochastic Gradient Descent Methods for Accelerated Non-Convex Optimization.
Multi-Scale Group Transformer for Long Sequence Modeling in Speech Separation.
EndCold: An End-to-End Framework for Cold Question Routing in Community Question Answering Services.
P-KDGAN: Progressive Knowledge Distillation with GANs for One-class Novelty Detection.
CDIMC-net: Cognitive Deep Incomplete Multi-view Clustering Network.
Label Enhancement for Label Distribution Learning via Prior Knowledge.
Discovering Subsequence Patterns for Next POI Recommendation.
Trajectory Similarity Learning with Auxiliary Supervision and Optimal Matching.
Joint Multi-view 2D Convolutional Neural Networks for 3D Object Classification.
Split to Be Slim: An Overlooked Redundancy in Vanilla Convolution.
One-Shot Neural Architecture Search via Novelty Driven Sampling.
Self-adaptive Re-weighted Adversarial Domain Adaptation.
BERT-INT: A BERT-based Interaction Model For Knowledge Graph Alignment.
Generating Robust Audio Adversarial Examples with Temporal Dependency.
Semi-supervised Clustering via Pairwise Constrained Optimal Graph.
Exploring Parameter Space with Structured Noise for Meta-Reinforcement Learning.
Dual Policy Distillation.
A Dual Input-aware Factorization Machine for CTR Prediction.
I²HRL: Interactive Influence-based Hierarchical Reinforcement Learning.
Weakly-Supervised Multi-view Multi-instance Multi-label Learning.
Gradient Perturbation is Underrated for Differentially Private Convex Optimization.
MULTIPOLAR: Multi-Source Policy Aggregation for Transfer Reinforcement Learning between Diverse Environmental Dynamics.
Greedy Convex Ensemble.
Efficient Deep Reinforcement Learning via Adaptive Policy Transfer.
Multi-Feedback Bandit Learning with Probabilistic Contexts.
On Metric DBSCAN with Low Doubling Dimension.
BaKer-Nets: Bayesian Random Kernel Mapping Networks.
MergeNAS: Merge Operations into One for Differentiable Architecture Search.
Discovering Latent Class Labels for Multi-Label Learning.
Analysis of Q-learning with Adaptation and Momentum Restart for Gradient Descent.
Bayesian Optimization using Pseudo-Points.
Hybrid Learning for Multi-agent Cooperation with Sub-optimal Demonstrations.
RDF-to-Text Generation with Graph-augmented Structural Neural Encoders.
User Modeling with Click Preference and Reading Satisfaction for News Recommendation.
Evaluating and Aggregating Feature-based Model Explanations.
Discriminative Feature Selection via A Structured Sparse Subspace Learning Module.
A Graphical and Attentional Framework for Dual-Target Cross-Domain Recommendation.
Towards Explainable Conversational Recommendation.
TransRHS: A Representation Learning Method for Knowledge Graphs with Relation Hierarchical Structure.
Classification with Rejection: Scaling Generative Classifiers with Supervised Deep Infomax.
Multi-View Attribute Graph Convolution Networks for Clustering.
Quadratic Sparse Gaussian Graphical Model Estimation Method for Massive Variables.
Asymmetric Distribution Measure for Few-shot Learning.
Unsupervised Representation Learning by Predicting Random Distances.
Learning From Multi-Dimensional Partial Labels.
Nearly Optimal Regret for Stochastic Linear Bandits with Heavy-Tailed Payoffs.
Triple-GAIL: A Multi-Modal Imitation Learning Framework with Generative Adversarial Nets.
Reducing Underflow in Mixed Precision Training by Gradient Scaling.
Class Prior Estimation in Active Positive and Unlabeled Learning.
Crowdsourcing with Multiple-Source Knowledge Transfer.
Independent Skill Transfer for Deep Reinforcement Learning.
Seq-U-Net: A One-Dimensional Causal U-Net for Efficient Sequence Modelling.
Learning in the Wild with Incremental Skeptical Gaussian Processes.
Multi-Class Imbalanced Graph Convolutional Network Learning.
Adaptively Multi-Objective Adversarial Training for Dialogue Generation.
Constrained Policy Improvement for Efficient Reinforcement Learning.
DACE: Distribution-Aware Counterfactual Explanation by Mixed-Integer Linear Optimization.
Reinforcement Learning Framework for Deep Brain Stimulation Study.
Spectral Pruning: Compressing Deep Neural Networks via Spectral Analysis and its Generalization Error.
Communicative Representation Learning on Attributed Molecular Graphs.
BRPO: Batch Residual Policy Optimization.
Reward Prediction Error as an Exploration Objective in Deep RL.
Mutual Information Estimation using LSH Sampling.
Exploiting Neuron and Synapse Filter Dynamics in Spatial Temporal Learning of Deep Spiking Neural Network.
Is the Skip Connection Provable to Reform the Neural Network Loss Landscape?
Temporal Attribute Prediction via Joint Modeling of Multi-Relational Structure Evolution.
Measuring the Discrepancy between Conditional Distributions: Methods, Properties and Applications.
General Purpose MRF Learning with Neural Network Potentials.
Deep Latent Low-Rank Fusion Network for Progressive Subspace Discovery.
Inference-Masked Loss for Deep Structured Output Learning.
Toward a neuro-inspired creative decoder.
KGNN: Knowledge Graph Neural Network for Drug-Drug Interaction Prediction.
Internal and Contextual Attention Network for Cold-start Multi-channel Matching in Recommendation.
Accelerating Stratified Sampling SGD by Reconstructing Strata.
Consistent MetaReg: Alleviating Intra-task Discrepancy for Better Meta-knowledge.
Only Relevant Information Matters: Filtering Out Noisy Samples To Boost RL.
Diffusion Variational Autoencoders.
SVRG for Policy Evaluation with Fewer Gradient Evaluations.
Explainable Recommendation via Interpretable Feature Mapping and Evaluation of Explainability.
Optimality, Accuracy, and Efficiency of an Exact Functional Test.
Learning Neural-Symbolic Descriptive Planning Models via Cube-Space Priors: The Voyage Home (to STRIPS).
I4R: Promoting Deep Reinforcement Learning by the Indicator for Expressive Representations.
Textual Membership Queries.
Self-Attentional Credit Assignment for Transfer in Reinforcement Learning.
Understanding the Power and Limitations of Teaching with Imperfect Knowledge.
The Importance of the Test Set Size in Quantification Assessment.
Mixed-Variable Bayesian Optimization.
On Deep Unsupervised Active Learning.
Feature Statistics Guided Efficient Filter Pruning.
Partial Multi-Label Learning via Multi-Subspace Representation.
A Bi-level Formulation for Label Noise Learning with Spectral Cluster Discovery.
Sinkhorn Regression.
Collaborative Self-Attention Network for Session-based Recommendation.
Beyond Network Pruning: a Joint Search-and-Training Approach.
Intent Preference Decoupling for User Representation on Online Recommender System.
Label Distribution for Learning with Noisy Labels.
Learning Personalized Itemset Mapping for Cross-Domain Recommendation.
Combinatorial Multi-Armed Bandits with Concave Rewards and Fairness Constraints.
Multivariate Probability Calibration with Isotonic Bernstein Polynomials.
Joint Partial Optimal Transport for Open Set Domain Adaptation.
Argot: Generating Adversarial Readable Chinese Texts.
Clarinet: A One-step Approach Towards Budget-friendly Unsupervised Domain Adaptation.
Deep Feedback Network for Recommendation.
Multi-label Feature Selection via Global Relevance and Redundancy Optimization.
Balancing Individual Preferences and Shared Objectives in Multiagent Reinforcement Learning.
Hypothesis Sketching for Online Kernel Selection in Continuous Kernel Space.
MaCAR: Urban Traffic Light Control via Active Multi-agent Communication and Action Rectification.
Contextualized Point-of-Interest Recommendation.
Collaboration Based Multi-Label Propagation for Fraud Detection.
Recurrent Dirichlet Belief Networks for interpretable Dynamic Relational Data Modelling.
AdaBERT: Task-Adaptive BERT Compression with Differentiable Neural Architecture Search.
Scalable Gaussian Process Regression Networks.
Neural Tensor Model for Learning Multi-Aspect Factors in Recommender Systems.
Embodied Multimodal Multitask Learning.
Convolutional Neural Networks with Compression Complexity Pooling for Out-of-Distribution Image Detection.
Synthesizing Aspect-Driven Recommendation Explanations from Reviews.
Towards a Hierarchical Bayesian Model of Multi-View Anomaly Detection.
Learning with Labeled and Unlabeled Multi-Step Transition Data for Recovering Markov Chain from Incomplete Transition Data.
Logic Constrained Pointer Networks for Interpretable Textual Similarity.
Generalized Mean Estimation in Monte-Carlo Tree Search.
Knowledge-Based Regularization in Generative Modeling.
Optimal Margin Distribution Machine for Multi-Instance Learning.
Privileged label enhancement with multi-label learning.
Tensor-based multi-view label enhancement for multi-label learning.
Arbitrary Talking Face Generation via Attentional Audio-Visual Coherence Learning.
LSGCN: Long Short-Term Traffic Prediction with Graph Convolutional Networks.
Unsupervised Monocular Visual-inertial Odometry Network.
Stochastic Batch Augmentation with An Effective Distilled Dynamic Soft Label Regularizer.
Intention2Basket: A Neural Intention-driven Approach for Dynamic Next-basket Planning.
DropNAS: Grouped Operation Dropout for Differentiable Architecture Search.
Interpretable Models for Understanding Immersive Simulations.
Complete Bottom-Up Predicate Invention in Meta-Interpretive Learning.
DeepView: Visualizing Classification Boundaries of Deep Neural Networks as Scatter Plots Using Discriminative Dimensionality Reduction.
Soft Threshold Ternary Networks.
KoGuN: Accelerating Deep Reinforcement Learning via Integrating Human Suboptimal Knowledge.
Randomised Gaussian Process Upper Confidence Bound for Bayesian Optimisation.
FNNC: Achieving Fairness through Neural Networks.
Towards Accurate and Robust Domain Adaptation under Noisy Environments.
Fairness-Aware Neural Rényi Minimization for Continuous Features.
Batch Decorrelation for Active Metric Learning.
Online Positive and Unlabeled Learning.
Disentangling Direct and Indirect Interactions in Polytomous Item Response Theory Models.
Human-Driven FOL Explanations of Deep Learning.
Effective Search of Logical Forms for Weakly Supervised Knowledge-Based Question Answering.
Best Arm Identification in Spectral Bandits.
Learning Interpretable Models in the Property Specification Language.
Can Cross Entropy Loss Be Robust to Label Noise?
Solving Hard AI Planning Instances Using Curriculum-Driven Deep Reinforcement Learning.
Knowledge Hypergraphs: Prediction Beyond Binary Relations.
Location Prediction over Sparse User Mobility Traces Using RNNs: Flashback in Hidden States!
Decorrelated Clustering with Data Selection Bias.
Memory Augmented Neural Model for Incremental Session-based Recommendation.
Metric Learning in Optimal Transport for Domain Adaptation.
Learning from Few Positives: a Provably Accurate Metric Learning Algorithm to Deal with Imbalanced Data.
Non-monotone DR-submodular Maximization over General Convex Sets.
Handling Black Swan Events in Deep Learning with Diversely Extrapolated Neural Networks.
Self-paced Consensus Clustering with Bipartite Graph.
Coloring Graph Neural Networks for Node Disambiguation.
Marthe: Scheduling the Learning Rate Via Online Hypergradients.
Direct Quantization for Training Highly Accurate Low Bit-width Deep Neural Networks.
The Sparse MinMax k-Means Algorithm for High-Dimensional Clustering.
Potential Driven Reinforcement Learning for Hard Exploration Tasks.
SI-VDNAS: Semi-Implicit Variational Dropout for Hierarchical One-shot Neural Architecture Search.
Fully Nested Neural Network for Adaptive Compression and Quantization.
Learning Large Logic Programs By Going Beyond Entailment.
Flow-based Intrinsic Curiosity Module.
Compressed Self-Attention for Deep Metric Learning with Low-Rank Approximation.
An Online Learning Framework for Energy-Efficient Navigation of Electric Vehicles.
Bayesian Decision Process for Budget-efficient Crowdsourced Clustering.
Variational Learning of Bayesian Neural Networks via Bayesian Dark Knowledge.
Switching Poisson Gamma Dynamical Systems.
IR-VIC: Unsupervised Discovery of Sub-goals for Transfer in RL.
Positive Unlabeled Learning with Class-prior Approximation.
Explainable Inference on Sequential Data via Memory-Tracking.
A New Attention Mechanism to Classify Multivariate Time Series.
Reinforcement Learning with Dynamic Boltzmann Softmax Updates.
Neural Representation and Learning of Hierarchical 2-additive Choquet Integrals.
Order-Dependent Event Models for Agent Interactions.
Learning Interpretable Representations with Informative Entanglements.
Learning With Subquadratic Regularization : A Primal-Dual Approach.
Stabilizing Adversarial Invariance Induction from Divergence Minimization Perspective.
Learning and Solving Regular Decision Processes.
Model-theoretic Characterizations of Existential Rule Languages.
Query Answering for Existential Rules via Efficient Datalog Rewriting.
Reasoning Like Human: Hierarchical Reinforcement Learning for Knowledge Graph Reasoning.
Tractable Fragments of Datalog with Metric Temporal Operators.
Ranking Semantics for Argumentation Systems With Necessities.
Adversarial Oracular Seq2seq Learning for Sequential Recommendation.
Threshold Treewidth and Hypertree Width.
Inconsistency Measurement for Improving Logical Formula Clustering.
Model-Based Synthesis of Incremental and Correct Estimators for Discrete Event Systems.
Concurrent Games in Dynamic Epistemic Logic.
On the Learnability of Possibilistic Theories.
Provenance for the Description Logic ELHr.
Controllability of Control Argumentation Frameworks.
Solving Analogies on Words based on Minimal Complexity Transformation.
A Fully Rational Account of Structured Argumentation Under Resource Bounds.
Lower Bounds for Approximate Knowledge Compilation.
A Journey into Ontology Approximation: From Non-Horn to Horn.
Cone Semantics for Logics with Negation.
On Robustness in Qualitative Constraint Networks.
A Modal Logic for Joint Abilities under Strategy Commitments.
On the Decidability of Intuitionistic Tense Logic without Disjunction.
Controlled Query Evaluation in Description Logics Through Instance Indistinguishability.
Lower Bounds and Faster Algorithms for Equality Constraints.
Rewriting the Description Logic ALCHIQ to Disjunctive Existential Rules.
On Computational Aspects of Iterated Belief Change.
Belief Merging Operators as Maximum Likelihood Estimators.
NeurASP: Embracing Neural Networks into Answer Set Programming.
Enriching Documents with Compact, Representative, Relevant Knowledge Graphs.
The Complexity Landscape of Resource-Constrained Scheduling.
Smart Voting.
Semantic Width and the Fixed-Parameter Tractability of Constraint Satisfaction Problems.
All-Instances Oblivious Chase Termination is Undecidable for Single-Head Binary TGDs.
Revisiting the Notion of Extension over Incomplete Abstract Argumentation Frameworks.
Automatic Synthesis of Generalized Winning Strategies of Impartial Combinatorial Games Using SMT Solvers.
A Logic of Directions.
Overcoming the Grounding Bottleneck Due to Constraints in ASP Solving: Constraints Become Propagators.
A Framework for Reasoning about Dynamic Axioms in Description Logics.
Synthesizing strategies under expected and exceptional environment behaviors.
Deep Learning for Abstract Argumentation Semantics.
Counting Query Answers over a DL-Lite Knowledge Base.
Switch-List Representations in a Knowledge Compilation Map.
Neural Entity Summarization with Joint Encoding and Weak Supervision.
Deductive Module Extraction for Expressive Description Logics.
Diagnosing Software Faults Using Multiverse Analysis.
Maximizing the Spread of an Opinion in Few Steps: Opinion Diffusion in Non-Binary Networks.
Implementing Theory of Mind on a Robot Using Dynamic Epistemic Logic.
Answering Counting Queries over DL-Lite Ontologies.
A Dataset Complexity Measure for Analogical Transfer.
Pitfalls of Learning a Reward Function Online.
Boolean Games: Inferring Agents' Goals Using Taxation Queries.
Improving Knowledge Tracing via Pre-training Question Embeddings.
Learning Regional Attention Convolutional Neural Network for Motion Intention Recognition Based on EEG Data.
Optimal Complex Task Assignment in Service Crowdsourcing.
Incorporating Failure Events in Agents' Decision Making to Improve User Satisfaction.
Incorporating Failure Events in Agents' Decision Making to Improve User Satisfaction.
Aggregating Crowd Wisdom with Side Information via a Clustering-based Label-aware Autoencoder.
Performance as a Constraint: An Improved Wisdom of Crowds Using Performance Regularization.
Learning to Complement Humans.
LISNN: Improving Spiking Neural Networks with Lateral Interactions for Robust Object Recognition.
Structured Probabilistic End-to-End Learning from Crowds.
NuCDS: An Efficient Local Search Algorithm for Minimum Connected Dominating Set.
Intelligent Virtual Machine Provisioning in Cloud Computing.
Exploration Based Language Learning for Text-Based Games.
Vertex Weighting-Based Tabu Search for p-Center Problem.
Self-Guided Evolution Strategies with Historical Estimated Gradients.
Two-goal Local Search and Inference Rules for Minimum Dominating Set.
Unsatisfiability Proofs for Weight 16 Codewords in Lam's Problem.
Bilinear Graph Neural Network with Neighbor Interactions.
Proximal Gradient Algorithm with Momentum and Flexible Parameter Restart for Nonconvex Optimization.
BANANA: when Behavior ANAlysis meets social Network Alignment.
Entity Synonym Discovery via Multipiece Bilateral Context Matching.
Joint Representation Learning of Legislator and Legislation for Roll Call Prediction.
Rumor Detection on Social Media with Graph Structured Adversarial Learning.
Domain Adaptive Classification on Heterogeneous Information Networks.
Graph Neural Architecture Search.
Improving Attention Mechanism in Graph Neural Networks via Cardinality Preservation.
Evidence-Aware Hierarchical Interactive Attention Networks for Explainable Claim Verification.
JANE: Jointly Adversarial Network Embedding.
Recovering Accurate Labeling Information from Partially Valid Data for Effective Multi-Label Learning.
Network Schema Preserving Heterogeneous Information Network Embedding.
Online Semi-supervised Multi-label Classification with Label Compression and Local Smooth Regression.
Multi-Channel Graph Neural Networks.
Understanding the Success of Graph-based Semi-Supervised Learning using Partially Labelled Stochastic Block Model.
Rebalancing Expanding EV Sharing Systems with Deep Reinforcement Learning.
A Sequential Convolution Network for Population Flow Prediction with Explicitly Correlation Modelling.
GraphSleepNet: Adaptive Spatial-Temporal Graph Convolutional Networks for Sleep Stage Classification.
GoGNN: Graph of Graphs Neural Network for Predicting Structured Entity Interactions.
A Spatial Missing Value Imputation Method for Multi-view Urban Statistical Data.
When Do GNNs Work: Understanding and Improving Neighborhood Aggregation.
Enhancing Urban Flow Maps via Neural ODEs.
Inductive Anomaly Detection on Attributed Networks.
Simultaneous Arrival Matching for New Spatial Crowdsourcing Platforms.
Speeding up Very Fast Decision Tree with Low Computational Cost.
On the Enumeration of Association Rules: A Decomposition-based Approach.
MR-GCN: Multi-Relational Graph Convolutional Networks based on Generalized Tensor Product.
Opinion Maximization in Social Trust Networks.
Robustness of Autoencoders for Anomaly Detection Under Adversarial Impact.
Motif-Preserving Temporal Network Embedding.
GraphFlow: Exploiting Conversation Flow with Graph Neural Networks for Conversational Machine Comprehension.
Discrete Embedding for Latent Networks.
Optimal Region Search with Submodular Maximization.
Inductive Link Prediction for Nodes Having Only Attribute Information.
Cause-Effect Association between Event Pairs in Event Datasets.
Automatic Dominance Breaking for a Class of Constraint Optimization Problems.
Bipartite Encoding: A New Binary Encoding for Solving Non-Binary CSPs.
NLocalSAT: Boosting Local Search with Solution Prediction.
Learning Optimal Decision Trees with MaxSAT and its Integration in AdaBoost.
Learning Sensitivity of RCPSP by Analyzing the Search Process.
Fast and Parallel Decomposition of Constraint Satisfaction Problems.
On Irrelevant Literals in Pseudo-Boolean Constraint Learning.
Extended Conjunctive Normal Form and An Efficient Algorithm for Cardinality Constraints.
Subgraph Isomorphism Meets Cutting Planes: Solving With Certified Solutions.
Early and Efficient Identification of Useless Constraint Propagation for Alldifferent Constraints.
Diversity of Solutions: An Exploration Through the Lens of Fixed-Parameter Tractability Theory.
A Graph-based Interactive Reasoning for Human-Object Interaction Detection.
Action-Guided Attention Mining and Relation Reasoning Network for Human-Object Interaction Detection.
Mucko: Multi-Layer Cross-Modal Knowledge Reasoning for Fact-based Visual Question Answering.
Multi-attention Meta Learning for Few-shot Fine-grained Image Recognition.
Overcoming Language Priors with Self-supervised Learning for Visual Question Answering.
Unsupervised Scene Adaptation with Memory Regularization in vivo.
Object-Aware Multi-Branch Relation Networks for Spatio-Temporal Video Grounding.
Video Question Answering on Screencast Tutorials.
Dress like an Internet Celebrity: Fashion Retrieval in Videos.
Cross-denoising Network against Corrupted Labels in Medical Image Segmentation with Domain Shift.
Weakly Supervised Local-Global Relation Network for Facial Expression Recognition.
CP-NAS: Child-Parent Neural Architecture Search for 1-bit CNNs.
A Similarity Inference Metric for RGB-Infrared Cross-Modality Person Re-identification.
Self-Supervised Tuning for Few-Shot Segmentation.
Co-Saliency Spatio-Temporal Interaction Network for Person Re-Identification in Videos.
Exploiting Visual Semantic Reasoning for Video-Text Retrieval.
Feature Augmented Memory with Global Attention Network for VideoQA.
HAF-SVG: Hierarchical Stochastic Video Generation with Aligned Features.
Progressive Domain-Independent Feature Decomposition Network for Zero-Shot Sketch-Based Image Retrieval.
TRP: Trained Rank Pruning for Efficient Deep Neural Networks.
DIDFuse: Deep Image Decomposition for Infrared and Visible Image Fusion.
Self-supervised Monocular Depth and Visual Odometry Learning with Scale-consistent Geometric Constraints.
Label-Attended Hashing for Multi-Label Image Retrieval.
Polar Relative Positional Encoding for Video-Language Segmentation.
Hierarchical Attention Based Spatial-Temporal Graph-to-Sequence Learning for Grounded Video Description.
Bidirectional Adversarial Training for Semi-Supervised Domain Adaptation.
Temporal Adaptive Alignment Network for Deep Video Inpainting.
Recurrent Relational Memory Network for Unsupervised Image Captioning.
Unsupervised Vehicle Re-identification with Progressive Adaptation.
Zero-Shot Object Detection via Learning an Embedding from Semantic Space to Visual Space.
Self-Supervised Gait Encoding with Locality-Aware Attention for Person Re-Identification.
Diagnosing the Environment Bias in Vision-and-Language Navigation.
Consistent Domain Structure Learning and Domain Alignment for 2D Image-Based 3D Objects Retrieval.
Detecting Adversarial Attacks via Subset Scanning of Autoencoder Activations and Reconstruction Error.
Overflow Aware Quantization: Accelerating Neural Network Inference by Low-bit Multiply-Accumulate Operations.
Weakly Supervised Few-shot Object Segmentation using Co-Attention with Visual and Semantic Embeddings.
Set and Rebase: Determining the Semantic Graph Connectivity for Unsupervised Cross-Modal Hashing.
Few-shot Human Motion Prediction via Learning Novel Motion Dynamics.
Hierarchical Instance Feature Alignment for 2D Image-Based 3D Shape Retrieval.
BARNet: Bilinear Attention Network with Adaptive Receptive Fields for Surgical Instrument Segmentation.
Deep Polarized Network for Supervised Learning of Accurate Binary Hashing Codes.
Dynamic Language Binding in Relational Visual Reasoning.
Few-shot Visual Learning with Contextual Memory and Fine-grained Calibration.
Transductive Relation-Propagation Network for Few-shot Learning.
Position-Aware Recalibration Module: Learning From Feature Semantics and Feature Position.
AttAN: Attention Adversarial Networks for 3D Point Cloud Semantic Segmentation.
Semi-Dynamic Hypergraph Neural Network for 3D Pose Estimation.
k-SDPP: Fixed-Size Video Summarization via Sequential Determinantal Point Processes.
Non-Autoregressive Image Captioning with Counterfactuals-Critical Multi-Agent Learning.
Latent Regularized Generative Dual Adversarial Network For Abnormal Detection.
Multi-Scale Spatial-Temporal Integration Convolutional Tube for Human Action Recognition.
Learning to Discretely Compose Reasoning Module Networks for Video Captioning.
Visual Encoding and Decoding of the Human Brain Based on Shared Features.
G2RL: Geometry-Guided Representation Learning for Facial Action Unit Intensity Estimation.
Bi-level Probabilistic Feature Learning for Deformable Image Registration.
Learning Task-aware Local Representations for Few-shot Learning.
TLPG-Tracker: Joint Learning of Target Localization and Proposal Generation for Visual Tracking.
E3SN: Efficient End-to-End Siamese Network for Video Object Segmentation.
Pay Attention to Devils: A Photometric Stereo Network for Better Details.
DAM: Deliberation, Abandon and Memory Networks for Generating Detailed and Non-repetitive Responses in Visual Dialogue.
GestureDet: Real-time Student Gesture Analysis with Multi-dimensional Attention-based Detector.
Channel Pruning via Automatic Structure Search.
Biased Feature Learning for Occlusion Invariant Face Recognition.
Human Consensus-Oriented Image Captioning.
Real-World Automatic Makeup via Identity Preservation Makeup Net.
Super-Resolution and Inpainting with Degraded and Upgraded Generative Adversarial Networks.
Multichannel Color Image Denoising via Weighted Schatten p-norm Minimization.
SBAT: Video Captioning with Sparse Boundary-Aware Transformer.
Generating Person Images with Appearance-aware Pose Stylizer.
Spatiotemporal Super-Resolution with Cross-Task Consistency and Its Semi-supervised Extension.
Characterizing Similarity of Visual Stimulus from Associated Neuronal Response.
SceneEncoder: Scene-Aware Semantic Segmentation of Point Clouds with A Learnable Scene Descriptor.
Bottom-up and Top-down: Bidirectional Additive Net for Edge Detection.
Learning from the Scene and Borrowing from the Rich: Tackling the Long Tail in Scene Graph Generation.
Multi-graph Fusion for Functional Neuroimaging Biomarker Detection.
SimPropNet: Improved Similarity Propagation for Few-shot Image Segmentation.
JPEG Artifacts Removal via Compression Quality Ranker-Guided Networks.
Large Scale Audiovisual Learning of Sounds with Weakly Labeled Data.
Lifelong Zero-Shot Learning.
Meta Segmentation Network for Ultra-Resolution Medical Images.
Deep Interleaved Network for Single Image Super-Resolution with Asymmetric Co-Attention.
GSM: Graph Similarity Model for Multi-Object Tracking.
SelectScale: Mining More Patterns from Images via Selective and Soft Dropout.
TextFuseNet: Scene Text Detection with Richer Fused Features.
When Pedestrian Detection Meets Nighttime Surveillance: A New Benchmark.
Reference Guided Face Component Editing.
A 3D Convolutional Approach to Spectral Object Segmentation in Space and Time.
Collaborative Learning of Depth Estimation, Visual Odometry and Camera Relocalization from Monocular Videos.
EViLBERT: Learning Task-Agnostic Multimodal Sense Embeddings.
Disentangled Feature Learning Network for Vehicle Re-Identification.
Channel-Level Variable Quantization Network for Deep Image Compression.
Metamorphic Testing and Certified Mitigation of Fairness Violations in NLP Models.
Relation-Based Counterfactual Explanations for Bayesian Network Classifiers.
Achieving Outcome Fairness in Machine Learning Models for Social Decision Problems.
Individual Fairness Revisited: Transferring Techniques from Adversarial Robustness.
WEFE: The Word Embeddings Fairness Evaluation Framework.
Sybil-proof Answer Querying Mechanism.
Modelling Bounded Rationality in Multi-Agent Interactions by Generalized Recursive Reasoning.
Monte-Carlo Tree Search for Scalable Coalition Formation.
Budgeted Facility Location Games with Strategic Facilities.
PeerNomination: Relaxing Exactness for Increased Accuracy in Peer Selection.
Participatory Budgeting with Project Interactions.
Competition Among Contests: a Safety Level Analysis.
When to Follow the Tip: Security Games with Strategic Informants.
The Competitive Effects of Variance-based Pricing.
A Multi-Objective Approach to Mitigate Negative Side Effects.
Altruism in Coalition Formation Games.
Model-Free Real-Time Autonomous Energy Management for a Residential Multi-Carrier Energy System: A Deep Reinforcement Learning Approach.
Efficient Algorithms for Learning Revenue-Maximizing Two-Part Tariffs.
Verifying Fault-Tolerance in Probabilistic Swarm Systems.
Keeping Your Friends Close: Land Allocation with Friends.
Combining Direct Trust and Indirect Trust in Multi-Agent Systems.
Computational Aspects of Conditional Minisum Approval Voting in Elections with Interdependent Issues.
A Deep Reinforcement Learning Approach to Concurrent Bilateral Negotiation.
Approximate Pareto Set for Fair and Efficient Allocation: Few Agent Types or Few Resource Types.
Partial Adversarial Behavior Deception in Security Games.
Tight Approximation for Proportional Approval Voting.
Learning Optimal Temperature Region for Solving Mixed Integer Functional DCOPs.
Convexity of b-matching Games.
A Penny for Your Thoughts: The Value of Communication in Ad Hoc Teamwork.
Dinkelbach-Type Algorithm for Computing Quantal Stackelberg Equilibrium.
Strategyproof Mechanism for Two Heterogeneous Facilities with Constant Approximation Ratio.
Incentive-Compatible Diffusion Auctions.
Selecting Voting Locations for Fun and Profit.
Synthesis of Deceptive Strategies in Reachability Games with Action Misperception.
Logics of Allies and Enemies: A Formal Approach to the Dynamics of Social Balance Theory.
The Complexity of Election Problems with Group-Separable Preferences.
Evaluating Committees for Representative Democracies: the Distortion and Beyond.
Well-Structured Committees.
Fair Division of Time: Multi-layered Cake Cutting.
Prophet Inequalities for Bayesian Persuasion.
Ethics, Prosperity, and Society: Moral Evaluation Using Virtue Ethics and Utilitarianism.
Maximizing Welfare with Incentive-Aware Evaluation Mechanisms.
Mechanism Design for School Choice with Soft Diversity Constraints.
Stable Matchings with Diversity Constraints: Affirmative Action is beyond NP.
Flow-Based Network Creation Games.
Proportionality in Approval-Based Elections With a Variable Number of Winners.
Peer-Prediction in the Presence of Outcome Dependent Lying Incentives.
Assume-Guarantee Synthesis for Prompt Linear Temporal Logic.
Concentration of Distortion: The Value of Extra Voters in Randomized Social Choice.
Strategic Campaign Management in Apportionment Elections.
Stable Roommate Problem with Diversity Preferences.
On the Complexity of Winner Verification and Candidate Winner for Multiwinner Voting Rules.
Decentralized MCTS via Learned Teammate Models.
Evaluating Approval-Based Multiwinner Voting in Terms of Robustness to Noise.
Fine-Grained View on Bribery for Group Identification.
Formalizing Group and Propagated Trust in Multi-Agent Systems.
Biased Opinion Dynamics: When the Devil is in the Details.
Uniform Welfare Guarantees Under Identical Subadditive Valuations.
Almost Group Envy-free Allocation of Indivisible Goods and Chores.
Speeding Up Incomplete GDL-based Algorithms for Multi-agent Optimization with Dense Local Utilities.
Maximum Nash Welfare and Other Stories About EFX.
Social Ranking Manipulability for the CP-Majority, Banzhaf and Lexicographic Excellence Solutions.
Intention Progression under Uncertainty.
An Algorithm for Multi-Attribute Diverse Matching.
