ijcai 2021 论文列表
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, IJCAI 2021, Virtual Event / Montreal, Canada, 19-27 August 2021.
|
IIAS: An Intelligent Insurance Assessment System through Online Real-time Conversation Analysis.
Communication-efficient and Scalable Decentralized Federated Edge Learning.
AutoBandit: A Meta Bandit Online Learning System.
Interactive Video Acquisition and Learning System for Motor Assessment of Parkinson's Disease.
Graph-Augmented Code Summarization in Computational Notebooks.
Predictive Analytics for COVID-19 Social Distancing.
Towards Fast and Accurate Multi-Person Pose Estimation on Mobile Devices.
Connect Multi-Agent Path Finding: Generation and Visualization.
VisioRed: A Visualisation Tool for Interpretable Predictive Maintenance.
A Compression-Compilation Framework for On-mobile Real-time BERT Applications.
InfOCF-Web: An Online Tool for Nonmonotonic Reasoning with Conditionals and Ranking Functions.
ConvLogMiner: A Real-Time Conversational Lifelog Miner.
HIVE: Hierarchical Information Visualization for Explainability.
Skills2Graph: Processing million Job Ads to face the Job Skill Mismatch Problem.
Web Interoperability for Ontology Development and Support with crowd 2.0.
A Neural Network Auction For Group Decision Making Over a Continuous Space.
Towards Fair and Transparent Algorithmic Systems.
Alleviating Road Traffic Congestion with Artificial Intelligence.
Towards a New Generation of Cognitive Diagnosis.
Width-Based Algorithms for Common Problems in Control, Planning and Reinforcement Learning.
Safe Weakly Supervised Learning.
Intelligent and Learning Agents: Four Investigations.
Adaptive Experimental Design for Optimizing Combinatorial Structures.
From Computational Social Choice to Digital Democracy.
Anomaly Mining - Past, Present and Future.
An Automated Framework for Supporting Data-Governance Rule Compliance in Decentralized MIMO Contexts.
Learning and Planning Under Uncertainty for Green Security.
Adversarial Examples in Physical World.
Data Efficient Algorithms and Interpretability Requirements for Personalized Assessment of Taskable AI Systems.
Learning from Multimedia Data with Incomplete Information.
Continual Lifelong Learning for Intelligent Agents.
A Human-AI Teaming Approach for Incremental Taxonomy Learning from Text.
Inter-Task Similarity for Lifelong Reinforcement Learning in Heterogeneous Tasks.
Modeling Institutions in Socio-Ecosystems.
Hardware-friendly Deep Learning by Network Quantization and Binarization.
Towards an Explainer-agnostic Conversational XAI.
On the Learnability of Knowledge in Multi-Agent Logics.
Combining Reinforcement Learning and Causal Models for Robotics Applications.
Uncertain Time Series Classification.
AI for Planning Public Health Interventions.
Deep Reinforcement Learning with Hierarchical Structures.
Nash Welfare in the Facility Location Problem.
Planning and Reinforcement Learning for General-Purpose Service Robots.
Robot Manipulation Learning Using Generative Adversarial Imitation Learning.
An Information-Theoretic Approach on Causal Structure Learning for Heterogeneous Data Characteristics of Real-World Scenarios.
Towards Robust Dynamic Network Embedding.
Safety Analysis of Deep Neural Networks.
Automated Facilitation Support in Online Forum.
Distributional Metareasoning for Heuristic Search.
Automatic Design of Heuristic Algorithms for Binary Optimization Problems.
Multi-agent Approach to Resource Allocation in Autonomous Vehicle Fleets.
Bottleneck Identification to Semantic Segmentation of Industrial 3D Point Cloud Scene via Deep Learning.
Greybox Algorithm Configuration.
Deep Residual Reinforcement Learning (Extended Abstract).
Semantic Linking Maps for Active Visual Object Search (Extended Abstract).
TAXOGAN: Hierarchical Network Representation Learning via Taxonomy Guided Generative Adversarial Networks (Extended Abstract).
Unsupervised Learning of Probably Symmetric Deformable 3D Objects from Images in the Wild (Extended Abstract).
Speech Recognition Using RFID Tattoos (Extended Abstract).
Open Intent Extraction from Natural Language Interactions (Extended Abstract).
RAFT: Recurrent All-Pairs Field Transforms for Optical Flow (Extended Abstract).
Imprecise Oracles Impose Limits to Predictability in Supervised Learning (Extended Abstract).
Politeness for the Theory of Algebraic Datatypes (Extended Abstract).
Beyond Accuracy: Behavioral Testing of NLP Models with Checklist (Extended Abstract).
Exploring the Effects of Goal Setting When Training for Complex Crowdsourcing Tasks (Extended Abstract).
Finding the Hardest Formulas for Resolution (Extended Abstract).
Unifying Online and Counterfactual Learning to Rank: A Novel Counterfactual Estimator that Effectively Utilizes Online Interventions (Extended Abstract).
Controlling Fairness and Bias in Dynamic Learning-to-Rank (Extended Abstract).
The Moodoo Library: Quantitative Metrics to Model How Teachers Make Use of the Classroom Space by Analysing Indoor Positioning Traces (Extended Abstract).
On Learning Sets of Symmetric Elements (Extended Abstract).
Revisiting Wedge Sampling for Budgeted Maximum Inner Product Search (Extended Abstract).
On Sampled Metrics for Item Recommendation (Extended Abstract).
Deep Drone Acrobatics (Extended Abstract).
Successor-Invariant First-Order Logic on Classes of Bounded Degree (Extended Abstract).
Mental Models of AI Agents in a Cooperative Game Setting (Extended Abstract).
Improved Guarantees and a Multiple-descent Curve for Column Subset Selection and the Nystrom Method (Extended Abstract).
Weaving a Semantic Web of Credibility Reviews for Explainable Misinformation Detection (Extended Abstract).
Decentralized No-regret Learning Algorithms for Extensive-form Correlated Equilibria (Extended Abstract).
Robust Domain Adaptation: Representations, Weights and Inductive Bias (Extended Abstract).
Abstract Cores in Implicit Hitting Set MaxSat Solving (Extended Abstract).
Comparing Weak Admissibility Semantics to their Dung-style Counterparts (Extended Abstract).
Defining the Semantics of Abstract Argumentation Frameworks through Logic Programs and Partial Stable Models (Extended Abstract).
Hierarchical Graph Traversal for Aggregate k Nearest Neighbors Search in Road Networks (Extended Abstract).
Cross-Domain Recommendation: Challenges, Progress, and Prospects.
Topic Modelling Meets Deep Neural Networks: A Survey.
Automated Machine Learning on Graphs: A Survey.
Deep Learning for Click-Through Rate Estimation.
A Survey on Universal Adversarial Attack.
A Comparative Survey: Benchmarking for Pool-based Active Learning.
Information-Theoretic Methods in Deep Neural Networks: Recent Advances and Emerging Opportunities.
Challenges and Opportunities of Building Fast GBDT Systems.
Time Series Data Augmentation for Deep Learning: A Survey.
Graph Learning based Recommender Systems: A Review.
A Survey on Low-Resource Neural Machine Translation.
Generalizing to Unseen Domains: A Survey on Domain Generalization.
A Survey on Response Selection for Retrieval-based Dialogues.
Tournaments in Computational Social Choice: Recent Developments.
A Unifying Bayesian Formulation of Measures of Interpretability in Human-AI Interaction.
Qualitative Spatial and Temporal Reasoning: Current Status and Future Challenges.
Neural Temporal Point Processes: A Review.
A Survey on Spoken Language Understanding: Recent Advances and New Frontiers.
Analogical Proportions: Why They Are Useful in AI.
Ten Years of BabelNet: A Survey.
Automated Fact-Checking for Assisting Human Fact-Checkers.
The Power of the Weisfeiler-Leman Algorithm for Machine Learning with Graphs.
Hybrid Probabilistic Inference with Logical and Algebraic Constraints: a Survey.
A Survey on Goal Recognition as Planning.
What's the Context? Implicit and Explicit Assumptions in Model-Based Goal Recognition.
Policy Learning with Constraints in Model-free Reinforcement Learning: A Survey.
Person Search Challenges and Solutions: A Survey.
Pretrained Language Model for Text Generation: A Survey.
A Survey on Complex Knowledge Base Question Answering: Methods, Challenges and Solutions.
End-to-End Constrained Optimization Learning: A Survey.
If Only We Had Better Counterfactual Explanations: Five Key Deficits to Rectify in the Evaluation of Counterfactual XAI Techniques.
Reasoning-Based Learning of Interpretable ML Models.
Optimal Transport for Deep Generative Models: State of the Art and Research Challenges.
Recent Advances in Heterogeneous Relation Learning for Recommendation.
Emerging Methods of Auction Design in Social Networks.
A Comprehensive Survey on Image Dehazing Based on Deep Learning.
Where Is Your Place, Visual Place Recognition?
Bayesian Nonparametric Space Partitions: A Survey.
Explanation in Constraint Satisfaction: A Survey.
Argumentative XAI: A Survey.
Understanding the Relationship between Interactions and Outcomes in Human-in-the-Loop Machine Learning.
Causal Learning for Socially Responsible AI.
Knowledge-aware Zero-Shot Learning: Survey and Perspective.
Mechanism Design for Facility Location Problems: A Survey.
Combinatorial Optimization and Reasoning with Graph Neural Networks.
When Computational Representation Meets Neuroscience: A Survey on Brain Encoding and Decoding.
Recent Trends in Word Sense Disambiguation: A Survey.
Hardware-Aware Neural Architecture Search: Survey and Taxonomy.
Recent Advances in Adversarial Training for Adversarial Robustness.
Building Affordance Relations for Robotic Agents - A Review.
Distortion in Social Choice Problems: The First 15 Years and Beyond.
A Survey of Machine Learning-Based Physics Event Generation.
Partition Function Estimation: A Quantitative Study.
Fast Algorithms for Relational Marginal Polytopes.
Provable Guarantees on the Robustness of Decision Rules to Causal Interventions.
Improved Acyclicity Reasoning for Bayesian Network Structure Learning with Constraint Programming.
BKT-POMDP: Fast Action Selection for User Skill Modelling over Tasks with Multiple Skills.
Deep Bucket Elimination.
Handling Overlaps When Lifting Gaussian Bayesian Networks.
On the Parameterized Complexity of Polytree Learning.
Non-Parametric Stochastic Sequential Assignment With Random Arrival Times.
The Traveling Tournament Problem with Maximum Tour Length Two: A Practical Algorithm with An Improved Approximation Bound.
TANGO: Commonsense Generalization in Predicting Tool Interactions for Mobile Manipulators.
The Fewer the Merrier: Pruning Preferred Operators with Novelty.
Solving Partially Observable Stochastic Shortest-Path Games.
Learning Generalized Unsolvability Heuristics for Classical Planning.
On Weak Stubborn Sets in Classical Planning.
Learning Temporal Plan Preferences from Examples: An Empirical Study.
Change the World - How Hard Can that Be? On the Computational Complexity of Fixing Planning Models.
Synthesizing Good-Enough Strategies for LTLf Specifications.
Dynamic Rebalancing Dockless Bike-Sharing System based on Station Community Discovery.
Anytime Multi-Agent Path Finding via Large Neighborhood Search.
Polynomial-Time in PDDL Input Size: Making the Delete Relaxation Feasible for Lifted Planning.
Online Learning of Action Models for PDDL Planning.
LTL-Constrained Steady-State Policy Synthesis.
Counterfactual Explanations for Optimization-Based Decisions in the Context of the GDPR.
Interference-free Walks in Time: Temporally Disjoint Paths.
Symbolic Dynamic Programming for Continuous State MDPs with Linear Program Transitions.
Incorporating Queueing Dynamics into Schedule-Driven Traffic Control.
Stochastic Probing with Increasing Precision.
Active Goal Recognition Design.
Custom-Design of FDR Encodings: The Case of Red-Black Planning.
Type-WA*: Using Exploration in Bounded Suboptimal Planning.
Learn to Intervene: An Adaptive Learning Policy for Restless Bandits in Application to Preventive Healthcare.
ME-MCTS: Online Generalization by Combining Multiple Value Estimators.
Efficient Black-Box Planning Using Macro-Actions with Focused Effects.
Relational Gating for "What If" Reasoning.
Drop Redundant, Shrink Irrelevant: Selective Knowledge Injection for Language Pretraining.
Document-level Relation Extraction as Semantic Segmentation.
Cross-Domain Slot Filling as Machine Reading Comprehension.
MRD-Net: Multi-Modal Residual Knowledge Distillation for Spoken Question Answering.
UniMF: A Unified Framework to Incorporate Multimodal Knowledge Bases intoEnd-to-End Task-Oriented Dialogue Systems.
Improving Stylized Neural Machine Translation with Iterative Dual Knowledge Transfer.
Knowledge-Aware Dialogue Generation via Hierarchical Infobox Accessing and Infobox-Dialogue Interaction Graph Network.
Learn from Syntax: Improving Pair-wise Aspect and Opinion Terms Extraction with Rich Syntactic Knowledge.
Hierarchical Modeling of Label Dependency and Label Noise in Fine-grained Entity Typing.
A Structure Self-Aware Model for Discourse Parsing on Multi-Party Dialogues.
A Sequence-to-Set Network for Nested Named Entity Recognition.
MEDA: Meta-Learning with Data Augmentation for Few-Shot Text Classification.
Learning Class-Transductive Intent Representations for Zero-shot Intent Detection.
MultiMirror: Neural Cross-lingual Word Alignment for Multilingual Word Sense Disambiguation.
A Streaming End-to-End Framework For Spoken Language Understanding.
Laughing Heads: Can Transformers Detect What Makes a Sentence Funny?
Multi-Hop Fact Checking of Political Claims.
Consistent Inference for Dialogue Relation Extraction.
Improving Text Generation with Dynamic Masking and Recovering.
Discourse-Level Event Temporal Ordering with Uncertainty-Guided Graph Completion.
Keep the Structure: A Latent Shift-Reduce Parser for Semantic Parsing.
Asynchronous Multi-grained Graph Network For Interpretable Multi-hop Reading Comprehension.
Modelling General Properties of Nouns by Selectively Averaging Contextualised Embeddings.
Enhancing Label Representations with Relational Inductive Bias Constraint for Fine-Grained Entity Typing.
ALaSca: an Automated approach for Large-Scale Lexical Substitution.
FedSpeech: Federated Text-to-Speech with Continual Learning.
Dialogue Disentanglement in Software Engineering: How Far are We?
Automatically Paraphrasing via Sentence Reconstruction and Round-trip Translation.
Dialogue Discourse-Aware Graph Model and Data Augmentation for Meeting Summarization.
Focus on Interaction: A Novel Dynamic Graph Model for Joint Multiple Intent Detection and Slot Filling.
Improving Context-Aware Neural Machine Translation with Source-side Monolingual Documents.
Generating Senses and RoLes: An End-to-End Model for Dependency- and Span-based Semantic Role Labeling.
Exemplification Modeling: Can You Give Me an Example, Please?
Objective-aware Traffic Simulation via Inverse Reinforcement Learning.
Long-term, Short-term and Sudden Event: Trading Volume Movement Prediction with Graph-based Multi-view Modeling.
CSGNN: Contrastive Self-Supervised Graph Neural Network for Molecular Interaction Prediction.
GraphMI: Extracting Private Graph Data from Graph Neural Networks.
Real-Time Pricing Optimization for Ride-Hailing Quality of Service.
SafeDrug: Dual Molecular Graph Encoders for Recommending Effective and Safe Drug Combinations.
Change Matters: Medication Change Prediction with Recurrent Residual Networks.
Towards Generating Summaries for Lexically Confusing Code through Code Erosion.
Solving Large-Scale Extensive-Form Network Security Games via Neural Fictitious Self-Play.
Hiding Numerical Vectors in Local Private and Shuffled Messages.
BACKDOORL: Backdoor Attack against Competitive Reinforcement Learning.
Hierarchical Adaptive Temporal-Relational Modeling for Stock Trend Prediction.
Adapting Meta Knowledge with Heterogeneous Information Network for COVID-19 Themed Malicious Repository Detection.
Learning Unknown from Correlations: Graph Neural Network for Inter-novel-protein Interaction Prediction.
Online Credit Payment Fraud Detection via Structure-Aware Hierarchical Recurrent Neural Network.
CFR-MIX: Solving Imperfect Information Extensive-Form Games with Combinatorial Action Space.
Traffic Congestion Alleviation over Dynamic Road Networks: Continuous Optimal Route Combination for Trip Query Streams.
Differentially Private Correlation Alignment for Domain Adaptation.
Dynamic Lane Traffic Signal Control with Group Attention and Multi-Timescale Reinforcement Learning.
Fine-tuning Is Not Enough: A Simple yet Effective Watermark Removal Attack for DNN Models.
Predictive Job Scheduling under Uncertain Constraints in Cloud Computing.
TrafficStream: A Streaming Traffic Flow Forecasting Framework Based on Graph Neural Networks and Continual Learning.
Parallel Subtrajectory Alignment over Massive-Scale Trajectory Data.
A Novel Sequence-to-Subgraph Framework for Diagnosis Classification.
Electrocardio Panorama: Synthesizing New ECG views with Self-supervision.
A Rule Mining-based Advanced Persistent Threats Detection System.
Multi-series Time-aware Sequence Partitioning for Disease Progression Modeling.
Boosting Offline Reinforcement Learning with Residual Generative Modeling.
Ordering-Based Causal Discovery with Reinforcement Learning.
Adaptive Residue-wise Profile Fusion for Low Homologous Protein Secondary Structure Prediction Using External Knowledge.
TEC: A Time Evolving Contextual Graph Model for Speaker State Analysis in Political Debates.
SPADE: A Semi-supervised Probabilistic Approach for Detecting Errors in Tables.
MDNN: A Multimodal Deep Neural Network for Predicting Drug-Drug Interaction Events.
Collaborative Graph Learning with Auxiliary Text for Temporal Event Prediction in Healthcare.
Solving Math Word Problems with Teacher Supervision.
Two-Sided Wasserstein Procrustes Analysis.
Self-Guided Community Detection on Networks with Missing Edges.
Sample Efficient Decentralized Stochastic Frank-Wolfe Methods for Continuous DR-Submodular Maximization.
Toward Optimal Solution for the Context-Attentive Bandit Problem.
MapGo: Model-Assisted Policy Optimization for Goal-Oriented Tasks.
You Get What You Sow: High Fidelity Image Synthesis with a Single Pretrained Network.
AutoReCon: Neural Architecture Search-based Reconstruction for Data-free Compression.
Multi-Target Invisibly Trojaned Networks for Visual Recognition and Detection.
Non-decreasing Quantile Function Network with Efficient Exploration for Distributional Reinforcement Learning.
Few-Shot Partial-Label Learning.
Uncertainty-aware Binary Neural Networks.
Graph Debiased Contrastive Learning with Joint Representation Clustering.
Automatic Mixed-Precision Quantization Search of BERT.
Uncertainty-Aware Few-Shot Image Classification.
Combining Tree Search and Action Prediction for State-of-the-Art Performance in DouDiZhu.
Neural Relation Inference for Multi-dimensional Temporal Point Processes via Message Passing Graph.
User Retention: A Causal Approach with Triple Task Modeling.
Rethink the Connections among Generalization, Memorization, and the Spectral Bias of DNNs.
Model-based Multi-agent Policy Optimization with Adaptive Opponent-wise Rollouts.
Non-I.I.D. Multi-Instance Learning for Predicting Instance and Bag Labels with Variational Auto-Encoder.
Private Stochastic Non-convex Optimization with Improved Utility Rates.
Correlation-Guided Representation for Multi-Label Text Classification.
UNBERT: User-News Matching BERT for News Recommendation.
Independence-aware Advantage Estimation.
Deep Descriptive Clustering.
Hindsight Trust Region Policy Optimization.
Graph Universal Adversarial Attacks: A Few Bad Actors Ruin Graph Learning Models.
Improving Sequential Recommendation Consistency with Self-Supervised Imitation.
Understanding the Effect of Bias in Deep Anomaly Detection.
Blocking-based Neighbor Sampling for Large-scale Graph Neural Networks.
Rethinking Label-Wise Cross-Modal Retrieval from A Semantic Sharing Perspective.
BESA: BERT-based Simulated Annealing for Adversarial Text Attacks.
Unsupervised Path Representation Learning with Curriculum Negative Sampling.
Progressive Open-Domain Response Generation with Multiple Controllable Attributes.
Secure Deep Graph Generation with Link Differential Privacy.
Multi-level Generative Models for Partial Label Learning with Non-random Label Noise.
A Clustering-based framework for Classifying Data Streams.
Decomposable-Net: Scalable Low-Rank Compression for Neural Networks.
Differentially Private Pairwise Learning Revisited.
Clustering-Induced Adaptive Structure Enhancing Network for Incomplete Multi-View Data.
KDExplainer: A Task-oriented Attention Model for Explaining Knowledge Distillation.
Evolutionary Gradient Descent for Non-convex Optimization.
k-Nearest Neighbors by Means of Sequence to Sequence Deep Neural Networks and Memory Networks.
Exploiting Spiking Dynamics with Spatial-temporal Feature Normalization in Graph Learning.
Learning Deeper Non-Monotonic Networks by Softly Transferring Solution Space.
Deep Reinforcement Learning Boosted Partial Domain Adaptation.
GSPL: A Succinct Kernel Model for Group-Sparse Projections Learning of Multiview Data.
Closing the BIG-LID: An Effective Local Intrinsic Dimensionality Defense for Nonlinear Regression Poisoning.
Reward-Constrained Behavior Cloning.
Reinforcement Learning Based Sparse Black-box Adversarial Attack on Video Recognition Models.
Robust Adversarial Imitation Learning via Adaptively-Selected Demonstrations.
Layer-Assisted Neural Topic Modeling over Document Networks.
Against Membership Inference Attack: Pruning is All You Need.
Self-Supervised Adversarial Distribution Regularization for Medication Recommendation.
Demiguise Attack: Crafting Invisible Semantic Adversarial Perturbations with Perceptual Similarity.
Mean Field Equilibrium in Multi-Armed Bandit Game with Continuous Reward.
Discrete Multiple Kernel k-means.
Stability and Generalization for Randomized Coordinate Descent.
Learn the Highest Label and Rest Label Description Degrees.
Multi-hop Attention Graph Neural Networks.
Probabilistic Sufficient Explanations.
Learning from Complementary Labels via Partial-Output Consistency Regularization.
Sensitivity Direction Learning with Neural Networks Using Domain Knowledge as Soft Shape Constraints.
Compositional Neural Logic Programming.
Dual Active Learning for Both Model and Data Selection.
Self-supervised Network Evolution for Few-shot Classification.
Hyperspectral Band Selection via Spatial-Spectral Weighted Region-wise Multiple Graph Fusion-Based Spectral Clustering.
Predicting Traffic Congestion Evolution: A Deep Meta Learning Approach.
Towards Reducing Biases in Combining Multiple Experts Online.
MFNP: A Meta-optimized Model for Few-shot Next POI Recommendation.
TE-ESN: Time Encoding Echo State Network for Prediction Based on Irregularly Sampled Time Series Data.
Neural Architecture Search of SPD Manifold Networks.
Positive-Unlabeled Learning from Imbalanced Data.
Online Risk-Averse Submodular Maximization.
Unsupervised Progressive Learning and the STAM Architecture.
Interpretable Compositional Convolutional Neural Networks.
Regularizing Variational Autoencoder with Diversity and Uncertainty Awareness.
Towards Robust Model Reuse in the Presence of Latent Domains.
Don't Do What Doesn't Matter: Intrinsic Motivation with Action Usefulness.
Physics-aware Spatiotemporal Modules with Auxiliary Tasks for Meta-Learning.
Stochastic Shortest Path with Adversarially Changing Costs.
Exact Acceleration of K-Means++ and K-Means||.
Source-free Domain Adaptation via Avatar Prototype Generation and Adaptation.
Multi-Agent Reinforcement Learning for Automated Peer-to-Peer Energy Trading in Double-Side Auction Market.
Multi-version Tensor Completion for Time-delayed Spatio-temporal Data.
Meta-Reinforcement Learning by Tracking Task Non-stationarity.
Learning Aggregation Functions.
Two Birds with One Stone: Series Saliency for Accurate and Interpretable Multivariate Time Series Forecasting.
Explaining Deep Neural Network Models with Adversarial Gradient Integration.
Learning Embeddings from Knowledge Graphs With Numeric Edge Attributes.
TIDOT: A Teacher Imitation Learning Approach for Domain Adaptation with Optimal Transport.
What Changed? Interpretable Model Comparison.
Accelerating Neural Architecture Search via Proxy Data.
Fine-grained Generalization Analysis of Structured Output Prediction.
Contrastive Losses and Solution Caching for Predict-and-Optimize.
Details (Don't) Matter: Isolating Cluster Information in Deep Embedded Spaces.
Minimization of Limit-Average Automata.
Evaluating Relaxations of Logic for Neural Networks: A Comprehensive Study.
Temporal and Object Quantification Networks.
Average-Reward Reinforcement Learning with Trust Region Methods.
Multi-Cause Effect Estimation with Disentangled Confounder Representation.
Hierarchical Temporal Multi-Instance Learning for Video-based Student Learning Engagement Assessment.
Stochastic Actor-Executor-Critic for Image-to-Image Translation.
Graph Entropy Guided Node Embedding Dimension Selection for Graph Neural Networks.
Transfer Learning via Optimal Transportation for Integrative Cancer Patient Stratification.
Smart Contract Vulnerability Detection: From Pure Neural Network to Interpretable Graph Feature and Expert Pattern Fusion.
Adversarial Spectral Kernel Matching for Unsupervised Time Series Domain Adaptation.
Two-stage Training for Learning from Label Proportions.
On the Intrinsic Differential Privacy of Bagging.
Graph Filter-based Multi-view Attributed Graph Clustering.
Residential Electric Load Forecasting via Attentive Transfer of Graph Neural Networks.
An Adaptive News-Driven Method for CVaR-sensitive Online Portfolio Selection in Non-Stationary Financial Markets.
SHPOS: A Theoretical Guaranteed Accelerated Particle Optimization Sampling Method.
Pairwise Half-graph Discrimination: A Simple Graph-level Self-supervised Strategy for Pre-training Graph Neural Networks.
Regularising Knowledge Transfer by Meta Functional Learning.
TextGTL: Graph-based Transductive Learning for Semi-supervised Text Classification via Structure-Sensitive Interpolation.
RetCL: A Selection-based Approach for Retrosynthesis via Contrastive Learning.
Topological Uncertainty: Monitoring Trained Neural Networks through Persistence of Activation Graphs.
On Guaranteed Optimal Robust Explanations for NLP Models.
Solving Continuous Control with Episodic Memory.
Towards Scalable Complete Verification of Relu Neural Networks via Dependency-based Branching.
Epsilon Best Arm Identification in Spectral Bandits.
Comparing Kullback-Leibler Divergence and Mean Squared Error Loss in Knowledge Distillation.
Knowledge Consolidation based Class Incremental Online Learning with Limited Data.
SalientSleepNet: Multimodal Salient Wave Detection Network for Sleep Staging.
Learning to Learn Personalized Neural Network for Ventricular Arrhythmias Detection on Intracardiac EGMs.
Learning CNF Theories Using MDL and Predicate Invention.
Reinforcement Learning for Route Optimization with Robustness Guarantees.
On Explaining Random Forests with SAT.
On the Neural Tangent Kernel of Deep Networks with Orthogonal Initialization.
Asynchronous Active Learning with Distributed Label Querying.
UniGNN: a Unified Framework for Graph and Hypergraph Neural Networks.
Behavior Mimics Distribution: Combining Individual and Group Behaviors for Federated Learning.
DEEPSPLIT: An Efficient Splitting Method for Neural Network Verification via Indirect Effect Analysis.
Interpretable Minority Synthesis for Imbalanced Classification.
Beyond the Spectrum: Detecting Deepfakes via Re-Synthesis.
State-Based Recurrent SPMNs for Decision-Theoretic Planning under Partial Observability.
Model-Based Reinforcement Learning for Infinite-Horizon Discounted Constrained Markov Decision Processes.
Fine-Grained Air Quality Inference via Multi-Channel Attention Model.
Riemannian Stochastic Recursive Momentum Method for non-Convex Optimization.
Enabling Retrain-free Deep Neural Network Pruning Using Surrogate Lagrangian Relaxation.
Robust Regularization with Adversarial Labelling of Perturbed Samples.
DA-GCN: A Domain-aware Attentive Graph Convolution Network for Shared-account Cross-domain Sequential Recommendation.
Hindsight Value Function for Variance Reduction in Stochastic Dynamic Environment.
Towards Understanding Deep Learning from Noisy Labels with Small-Loss Criterion.
Learning Nash Equilibria in Zero-Sum Stochastic Games via Entropy-Regularized Policy Approximation.
The Successful Ingredients of Policy Gradient Algorithms.
Hierarchical Class-Based Curriculum Loss.
InverseNet: Augmenting Model Extraction Attacks with Training Data Inversion.
Fast Multi-label Learning.
Bayesian Experience Reuse for Learning from Multiple Demonstrators.
Method of Moments for Topic Models with Mixed Discrete and Continuous Features.
BOBCAT: Bilevel Optimization-Based Computerized Adaptive Testing.
Video Summarization via Label Distributions Dual-Reward.
Learning Groupwise Explanations for Black-Box Models.
On the Convergence of Stochastic Compositional Gradient Descent Ascent Method.
Deep Reinforcement Learning for Multi-contact Motion Planning of Hexapod Robots.
Contrastive Model Invertion for Data-Free Knolwedge Distillation.
BAMBOO: A Multi-instance Multi-label Approach Towards VDI User Logon Behavior Modeling.
Jointly Learning Prices and Product Features.
Time-Series Representation Learning via Temporal and Contextual Contrasting.
Automatic Translation of Music-to-Dance for In-Game Characters.
Boosting Variational Inference With Locally Adaptive Step-Sizes.
Optimal ANN-SNN Conversion for Fast and Accurate Inference in Deep Spiking Neural Networks.
Graph-Free Knowledge Distillation for Graph Neural Networks.
Isotonic Data Augmentation for Knowledge Distillation.
Convexified Graph Neural Networks for Distributed Control in Robotic Swarms.
CuCo: Graph Representation with Curriculum Contrastive Learning.
Variational Model-based Policy Optimization.
Time-Aware Multi-Scale RNNs for Time Series Modeling.
On Self-Distilling Graph Neural Network.
Few-Shot Learning with Part Discovery and Augmentation from Unlabeled Images.
Dependent Multi-Task Learning with Causal Intervention for Image Captioning.
Monte Carlo Filtering Objectives.
Understanding Structural Vulnerability in Graph Convolutional Networks.
Learning Attributed Graph Representation with Communicative Message Passing Transformer.
AMA-GCN: Adaptive Multi-layer Aggregation Graph Convolutional Network for Disease Prediction.
Generative Adversarial Neural Architecture Search.
Reinforcement Learning for Sparse-Reward Object-Interaction Tasks in a First-person Simulated 3D Environment.
Thompson Sampling for Bandits with Clustered Arms.
Towards Understanding the Spectral Bias of Deep Learning.
Partial Multi-Label Optimal Margin Distribution Machine.
Fast Pareto Optimization for Subset Selection with Dynamic Cost Constraints.
Efficient Neural Network Verification via Layer-based Semidefinite Relaxations and Linear Cuts.
Optimal Algorithms for Range Searching over Multi-Armed Bandits.
Reconciling Rewards with Predictive State Representations.
Robustly Learning Composable Options in Deep Reinforcement Learning.
Verifying Reinforcement Learning up to Infinity.
DEHB: Evolutionary Hyberband for Scalable, Robust and Efficient Hyperparameter Optimization.
Conditional Self-Supervised Learning for Few-Shot Classification.
Deep Reinforcement Learning for Navigation in AAA Video Games.
Simulation of Electron-Proton Scattering Events by a Feature-Augmented and Transformed Generative Adversarial Network (FAT-GAN).
Likelihood-free Out-of-Distribution Detection with Invertible Generative Models.
The Surprising Power of Graph Neural Networks with Random Node Initialization.
AMEIR: Automatic Behavior Modeling, Interaction Exploration and MLP Investigation in the Recommender System.
Causal Discovery with Multi-Domain LiNGAM for Latent Factors.
Neighborhood Intervention Consistency: Measuring Confidence for Knowledge Graph Link Prediction.
Transforming Robotic Plans with Timed Automata to Solve Temporal Platform Constraints.
Abstract Argumentation Frameworks with Domain Assignments.
Skeptical Reasoning with Preferred Semantics in Abstract Argumentation without Computing Preferred Extensions.
Lifting Symmetry Breaking Constraints with Inductive Logic Programming.
Physics-informed Spline Learning for Nonlinear Dynamics Discovery.
Ranking Extensions in Abstract Argumentation.
A Description Logic for Analogical Reasoning.
Inconsistency Measurement for Paraconsistent Inference.
Efficient PAC Reinforcement Learning in Regular Decision Processes.
Unsupervised Knowledge Graph Alignment by Probabilistic Reasoning and Semantic Embedding.
A Ladder of Causal Distances.
Modeling Precomputation In Games Played Under Computational Constraints.
Compressing Exact Cover Problems with Zero-suppressed Binary Decision Diagrams.
Two Forms of Responsibility in Strategic Games.
Faster Smarter Proof by Induction in Isabelle/HOL.
On the Relation Between Approximation Fixpoint Theory and Justification Theory.
Bounded Predicates in Description Logics with Counting.
Multi-Agent Belief Base Revision.
Reasoning about Beliefs and Meta-Beliefs by Regression in an Expressive Probabilistic Action Logic.
Inferring Time-delayed Causal Relations in POMDPs from the Principle of Independence of Cause and Mechanism.
Scalable Non-observational Predicate Learning in ASP.
Signature-Based Abduction with Fresh Individuals and Complex Concepts for Description Logics.
Multi-Agent Abstract Argumentation Frameworks With Incomplete Knowledge of Attacks.
HIP Network: Historical Information Passing Network for Extrapolation Reasoning on Temporal Knowledge Graph.
Using Platform Models for a Guided Explanatory Diagnosis Generation for Mobile Robots.
Updating the Belief Promotion Operator.
Program Synthesis as Dependency Quantified Formula Modulo Theory.
Actively Learning Concepts and Conjunctive Queries under ELr-Ontologies.
Decomposition-Guided Reductions for Argumentation and Treewidth.
Improved Algorithms for Allen's Interval Algebra: a Dynamic Programming Approach.
How Hard to Tell? Complexity of Belief Manipulation Through Propositional Announcements.
HyperLDLf: a Logic for Checking Properties of Finite Traces Process Logs.
Finite-Trace and Generalized-Reactivity Specifications in Temporal Synthesis.
Abductive Knowledge Induction from Raw Data.
A Uniform Abstraction Framework for Generalized Planning.
On Belief Change for Multi-Label Classifier Encodings.
Intensional and Extensional Views in DL-Lite Ontologies.
Abductive Learning with Ground Knowledge Base.
Budget-Constrained Coalition Strategies with Discounting.
Cardinality Queries over DL-Lite Ontologies.
Choice Logics and Their Computational Properties.
Reasoning About Agents That May Know Other Agents' Strategies.
On Cycles, Attackers and Supporters - A Contribution to The Investigation of Dynamics in Abstract Argumentation.
A Game-Theoretic Account of Responsibility Allocation.
Best-Effort Synthesis: Doing Your Best Is Not Harder Than Giving Up.
Type Anywhere You Want: An Introduction to Invisible Mobile Keyboard.
Item Response Ranking for Cognitive Diagnosis.
Event-based Action Recognition Using Motion Information and Spiking Neural Networks.
An Entanglement-driven Fusion Neural Network for Video Sentiment Analysis.
Accounting for Confirmation Bias in Crowdsourced Label Aggregation.
Human-AI Collaboration with Bandit Feedback.
Pruning of Deep Spiking Neural Networks through Gradient Rewiring.
UIBert: Learning Generic Multimodal Representations for UI Understanding.
Choosing the Right Algorithm With Hints From Complexity Theory.
A New Upper Bound Based on Vertex Partitioning for the Maximum K-plex Problem.
A Runtime Analysis of Typical Decomposition Approaches in MOEA/D Framework for Many-objective Optimization Problems.
Bounded-cost Search Using Estimates of Uncertainty.
DACBench: A Benchmark Library for Dynamic Algorithm Configuration.
Faster Guarantees of Evolutionary Algorithms for Maximization of Monotone Submodular Functions.
Knowledge-based Residual Learning.
Graph Deformer Network.
Heterogeneous Graph Information Bottleneck.
Spatial-Temporal Sequential Hypergraph Network for Crime Prediction with Dynamic Multiplex Relation Learning.
User-as-Graph: User Modeling with Heterogeneous Graph Pooling for News Recommendation.
Federated Learning with Fair Averaging.
Preference-Adaptive Meta-Learning for Cold-Start Recommendation.
Heuristic Search for Approximating One Matrix in Terms of Another Matrix.
Pattern-enhanced Contrastive Policy Learning Network for Sequential Recommendation.
Cooperative Joint Attentive Network for Patient Outcome Prediction on Irregular Multi-Rate Multivariate Health Data.
Does Every Data Instance Matter? Enhancing Sequential Recommendation by Eliminating Unreliable Data.
LDP-FL: Practical Private Aggregation in Federated Learning with Local Differential Privacy.
Federated Model Distillation with Noise-Free Differential Privacy.
Keyword-Based Knowledge Graph Exploration Based on Quadratic Group Steiner Trees.
Masked Label Prediction: Unified Message Passing Model for Semi-Supervised Classification.
GAEN: Graph Attention Evolving Networks.
Graph Edit Distance Learning via Modeling Optimum Matchings with Constraints.
GraphReach: Position-Aware Graph Neural Network using Reachability Estimations.
Node-wise Localization of Graph Neural Networks.
MG-DVD: A Real-time Framework for Malware Variant Detection Based on Dynamic Heterogeneous Graph Learning.
RCA: A Deep Collaborative Autoencoder Approach for Anomaly Detection.
Modeling Trajectories with Neural Ordinary Differential Equations.
Discovering Collaborative Signals for Next POI Recommendation with Iterative Seq2Graph Augmentation.
Practical One-Shot Federated Learning for Cross-Silo Setting.
Multi-Scale Contrastive Siamese Networks for Self-Supervised Graph Representation Learning.
Temporal Heterogeneous Information Network Embedding.
Federated Learning with Sparsification-Amplified Privacy and Adaptive Optimization.
Learning Stochastic Equivalence based on Discrete Ricci Curvature.
Guided Attention Network for Concept Extraction.
Multi-Channel Pooling Graph Neural Networks.
Masked Contrastive Learning for Anomaly Detection.
Exploring Periodicity and Interactivity in Multi-Interest Framework for Sequential Recommendation.
Computing Optimal Hypertree Decompositions with SAT.
Learning Implicitly with Noisy Data in Linear Arithmetic.
Backdoor DNFs.
Solving Graph Homomorphism and Subgraph Isomorphism Problems Faster Through Clique Neighbourhood Constraints.
Decomposition Strategies to Count Integer Solutions over Linear Constraints.
Efficiently Explaining CSPs with Unsatisfiable Subset Optimization.
Improved CP-Based Lagrangian Relaxation Approach with an Application to the TSP.
Reducing SAT to Max2SAT.
PoseGTAC: Graph Transformer Encoder-Decoder with Atrous Convolution for 3D Human Pose Estimation.
A Sketch-Transformer Network for Face Photo-Sketch Synthesis.
PointLIE: Locally Invertible Embedding for Point Cloud Sampling and Recovery.
Rescuing Deep Hashing from Dead Bits Problem.
Sequential 3D Human Pose Estimation Using Adaptive Point Cloud Sampling Strategy.
Context-Aware Image Inpainting with Learned Semantic Priors.
What If We Could Not See? Counterfactual Analysis for Egocentric Action Anticipation.
Learning Implicit Temporal Alignment for Few-shot Video Classification.
Removing Foreground Occlusions in Light Field using Micro-lens Dynamic Filter.
Low Resolution Information Also Matters: Learning Multi-Resolution Representations for Person Re-Identification.
Detecting Deepfake Videos with Temporal Dropout 3DCNN.
Dual-Cross Central Difference Network for Face Anti-Spoofing.
CogTree: Cognition Tree Loss for Unbiased Scene Graph Generation.
EmbedMask: Embedding Coupling for Instance Segmentation.
Multimodal Transformer Networks for Pedestrian Trajectory Prediction.
Adv-Makeup: A New Imperceptible and Transferable Attack on Face Recognition.
Object Detection in Densely Packed Scenes via Semi-Supervised Learning with Dual Consistency.
Coupling Intent and Action for Pedestrian Crossing Behavior Prediction.
Non-contact Pain Recognition from Video Sequences with Remote Physiological Measurements Prediction.
RR-Net: Injecting Interactive Semantics in Human-Object Interaction Detection.
Hierarchical Self-supervised Augmented Knowledge Distillation.
Tool- and Domain-Agnostic Parameterization of Style Transfer Effects Leveraging Pretrained Perceptual Metrics.
Adversarial Feature Disentanglement for Long-Term Person Re-identification.
Segmenting Transparent Objects in the Wild with Transformer.
Micro-Expression Recognition Enhanced by Macro-Expression from Spatial-Temporal Domain.
GM-MLIC: Graph Matching based Multi-Label Image Classification.
Weakly-Supervised Spatio-Temporal Anomaly Detection in Surveillance Video.
Tracklet Proposal Network for Multi-Object Tracking on Point Clouds.
Weakly Supervised Dense Video Captioning via Jointly Usage of Knowledge Distillation and Cross-modal Matching.
Local Representation is Not Enough: Soft Point-Wise Transformer for Descriptor and Detector of Local Features.
Domain-Smoothing Network for Zero-Shot Sketch-Based Image Retrieval.
HifiFace: 3D Shape and Semantic Prior Guided High Fidelity Face Swapping.
Deep Unified Cross-Modality Hashing by Pairwise Data Alignment.
Towards Compact Single Image Super-Resolution via Contrastive Self-distillation.
Dig into Multi-modal Cues for Video Retrieval with Hierarchical Alignment.
Norm-guided Adaptive Visual Embedding for Zero-Shot Sketch-Based Image Retrieval.
Audio2Head: Audio-driven One-shot Talking-head Generation with Natural Head Motion.
Spline Positional Encoding for Learning 3D Implicit Signed Distance Fields.
Tag, Copy or Predict: A Unified Weakly-Supervised Learning Framework for Visual Information Extraction using Sequences.
Cross-Domain Few-Shot Classification via Adversarial Task Augmentation.
Text-based Person Search via Multi-Granularity Embedding Learning.
Learning Interpretable Concept Groups in CNNs.
Towards Cross-View Consistency in Semantic Segmentation While Varying View Direction.
AVA: Adversarial Vignetting Attack against Visual Recognition.
MatchVIE: Exploiting Match Relevancy between Entities for Visual Information Extraction.
Proposal-free One-stage Referring Expression via Grid-Word Cross-Attention.
Context-aware Cross-level Fusion Network for Camouflaged Object Detection.
Speech2Talking-Face: Inferring and Driving a Face with Synchronized Audio-Visual Representation.
Enhance Image as You Like with Unpaired Learning.
Towards Unsupervised Deformable-Instances Image-to-Image Translation.
Structure Guided Lane Detection.
Learning with Selective Forgetting.
Learning Visual Words for Weakly-Supervised Semantic Segmentation.
Multi-Level Graph Encoding with Structural-Collaborative Relation Learning for Skeleton-Based Person Re-Identification.
Adaptive Edge Attention for Graph Matching with Outliers.
Unsupervised Hashing with Contrastive Information Bottleneck.
SiamRCR: Reciprocal Classification and Regression for Visual Object Tracking.
Self-boosting for Feature Distillation.
Few-shot Neural Human Performance Rendering from Sparse RGBD Videos.
Attention-based Pyramid Dilated Lattice Network for Blind Image Denoising.
Look Wide and Interpret Twice: Improving Performance on Interactive Instruction-following Tasks.
Modality-aware Style Adaptation for RGB-Infrared Person Re-Identification.
Point-based Acoustic Scattering for Interactive Sound Propagation via Surface Encoding.
CIMON: Towards High-quality Hash Codes.
One-Shot Affordance Detection.
Learn from Concepts: Towards the Purified Memory for Few-shot Learning.
Domain Generalization under Conditional and Label Shifts via Variational Bayesian Inference.
Graph Consistency Based Mean-Teaching for Unsupervised Domain Adaptive Person Re-Identification.
Dual Reweighting Domain Generalization for Face Presentation Attack Detection.
Bipartite Matching for Crowd Counting with Point Supervision.
Learning 3-D Human Pose Estimation from Catadioptric Videos.
A Multi-Constraint Similarity Learning with Adaptive Weighting for Visible-Thermal Person Re-Identification.
Direct Measure Matching for Crowd Counting.
Noise2Grad: Extract Image Noise to Denoise.
Instance-Aware Coherent Video Style Transfer for Chinese Ink Wash Painting.
PIANO: A Parametric Hand Bone Model from Magnetic Resonance Imaging.
Medical Image Segmentation using Squeeze-and-Expansion Transformers.
Deep Automatic Natural Image Matting.
IMENet: Joint 3D Semantic Scene Completion and 2D Semantic Segmentation through Iterative Mutual Enhancement.
Noise Doesn't Lie: Towards Universal Detection of Deep Inpainting.
Information Bottleneck Approach to Spatial Attention Learning.
Planning with Learned Dynamic Model for Unsupervised Point Cloud Registration.
Step-Wise Hierarchical Alignment Network for Image-Text Matching.
Perturb, Predict & Paraphrase: Semi-Supervised Learning using Noisy Student for Image Captioning.
Self-Supervised Video Representation Learning with Constrained Spatiotemporal Jigsaw.
AgeFlow: Conditional Age Progression and Regression with Normalizing Flows.
Dynamic Inconsistency-aware DeepFake Video Detection.
Multi-Scale Selective Feedback Network with Dual Loss for Real Image Denoising.
DeepME: Deep Mixture Experts for Large-scale Image Classification.
Disentangled Face Attribute Editing via Instance-Aware Latent Space Search.
AdaVQA: Overcoming Language Priors with Adapted Margin Cosine Loss.
EventDrop: Data Augmentation for Event-based Learning.
Self-Supervised Video Action Localization with Adversarial Temporal Transforms.
Learning Spectral Dictionary for Local Representation of Mesh.
Multi-view Feature Augmentation with Adaptive Class Activation Mapping.
Feature Space Targeted Attacks by Statistic Alignment.
Chop Chop BERT: Visual Question Answering by Chopping VisualBERT's Heads.
TCIC: Theme Concepts Learning Cross Language and Vision for Image Captioning.
Direction-aware Feature-level Frequency Decomposition for Single Image Deraining.
Phonovisual Biases in Language: is the Lexicon Tied to the Visual World?
Hierarchical Object-oriented Spatio-Temporal Reasoning for Video Question Answering.
Boundary Knowledge Translation based Reference Semantic Segmentation.
Leveraging Human Attention in Novel Object Captioning.
Zero-Shot Chinese Character Recognition with Stroke-Level Decomposition.
Novelty Detection via Contrastive Learning with Negative Data Augmentation.
Themis: A Fair Evaluation Platform for Computer Vision Competitions.
Explaining Self-Supervised Image Representations with Visual Probing.
GASP: Gated Attention for Saliency Prediction.
Characteristic Examples: High-Robustness, Low-Transferability Fingerprinting of Neural Networks.
An Examination of Fairness of AI Models for Deepfake Detection.
Decision Making with Differential Privacy under a Fairness Lens.
Bias Silhouette Analysis: Towards Assessing the Quality of Bias Metrics for Word Embedding Models.
Multi-Objective Reinforcement Learning for Designing Ethical Environments.
Addressing the Long-term Impact of ML Decisions via Policy Regret.
Location Predicts You: Location Prediction via Bi-direction Speculation and Dual-level Association.
On Smoother Attributions using Neural Stochastic Differential Equations.
Interacting with Explanations through Critiquing.
Data-Efficient Reinforcement Learning for Malaria Control.
MFVFD: A Multi-Agent Q-Learning Approach to Cooperative and Non-Cooperative Tasks.
Altruism Design in Networked Public Goods Games.
Dominant Resource Fairness with Meta-Types.
H-FL: A Hierarchical Communication-Efficient and Privacy-Protected Architecture for Federated Learning.
Learning with Generated Teammates to Achieve Type-Free Ad-Hoc Teamwork.
Budget-feasible Maximum Nash Social Welfare is Almost Envy-free.
State-Aware Value Function Approximation with Attention Mechanism for Restless Multi-armed Bandits.
Manipulation of k-Coalitional Games on Social Networks.
An Axiom System for Feedback Centralities.
Emergent Prosociality in Multi-Agent Games Through Gifting.
Reducing Bus Bunching with Asynchronous Multi-Agent Reinforcement Learning.
Fair Pairwise Exchange among Groups.
New Algorithms for Japanese Residency Matching.
Game-theoretic Analysis of Effort Allocation of Contributors to Public Projects.
Vitality Indices are Equivalent to Induced Game-Theoretic Centralities.
Tango: Declarative Semantics for Multiagent Communication Protocols.
Stochastic Market Games.
Matchings with Group Fairness Constraints: Online and Offline Algorithms.
Shortlisting Rules and Incentives in an End-to-End Model for Participatory Budgeting.
Data-Driven Methods for Balancing Fairness and Efficiency in Ride-Pooling.
Mean Field Games Flock! The Reinforcement Learning Way.
Majority Vote in Social Networks: Make Random Friends or Be Stubborn to Overpower Elites.
Winner Determination and Strategic Control in Conditional Approval Voting.
Almost Envy-Freeness for Groups: Improved Bounds via Discrepancy Theory.
Generalized Kings and Single-Elimination Winners in Random Tournaments.
Improving Welfare in One-Sided Matchings using Simple Threshold Queries.
Budget-feasible Mechanisms for Representing Groups of Agents Proportionally.
Strategyproof Randomized Social Choice for Restricted Sets of Utility Functions.
Fairness in Long-Term Participatory Budgeting.
Two-Stage Facility Location Games with Strategic Clients and Facilities.
Interaction Considerations in Learning from Humans.
Participatory Budgeting with Project Groups.
A Polynomial-time, Truthful, Individually Rational and Budget Balanced Ridesharing Mechanism.
Dynamic Proportional Rankings.
SURPRISE! and When to Schedule It.
Surprisingly Popular Voting Recovers Rankings, Surprisingly!
Guaranteeing Maximin Shares: Some Agents Left Behind.
Accomplice Manipulation of the Deferred Acceptance Algorithm.
Fair and Efficient Resource Allocation with Partial Information.
Even More Effort Towards Improved Bounds and Fixed-Parameter Tractability for Multiwinner Rules.
Worst-case Bounds on Power vs. Proportion in Weighted Voting Games with Application to False-name Manipulation.
Two-Sided Matching Meets Fair Division.
Kemeny Consensus Complexity.
Reasoning over Argument-Incomplete AAFs in the Presence of Correlations.
Relaxed Core Stability in Fractional Hedonic Games.
On a Competitive Secretary Problem with Deferred Selections.
Keep Your Distance: Land Division With Separation.
Graphical Cake Cutting via Maximin Share.
Online Selection of Diverse Committees.
Neural Regret-Matching for Distributed Constraint Optimization Problems.
The Parameterized Complexity of Connected Fair Division.
Multi-Agent Intention Progression with Black-Box Agents.
Improving Multi-agent Coordination by Learning to Estimate Contention.
Identifying Norms from Observation Using MCMC Sampling.
Learning in Markets: Greed Leads to Chaos but Following the Price is Right.
Cooperation in Threshold Public Projects with Binary Actions.
Temporal Induced Self-Play for Stochastic Bayesian Games.
Fractional Matchings under Preferences: Stability and Optimality.
Picking Sequences and Monotonicity in Weighted Fair Division.
Approximating the Shapley Value Using Stratified Empirical Bernstein Sampling.
Loyalty in Cardinal Hedonic Games.
Putting a Compass on the Map of Elections.
Winner Robustness via Swap- and Shift-Bribery: Parameterized Counting Complexity and Experiments.
Two Influence Maximization Games on Graphs Made Temporal.
Combining Fairness and Optimality when Selecting and Allocating Projects.
Learning Within an Instance for Designing High-Revenue Combinatorial Auctions.
PROPm Allocations of Indivisible Goods to Multiple Agents.
School Choice with Flexible Diversity Goals and Specialized Seats.
Diversity in Kemeny Rank Aggregation: A Parameterized Approach.
Distance Polymatrix Coordination Games.
