ijcai 2019 论文列表
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, IJCAI 2019, Macao, China, August 10-16, 2019.
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Intelligent Decision Support for Improving Power Management.
ATTENet: Detecting and Explaining Suspicious Tax Evasion Groups.
DeepRec: An Open-source Toolkit for Deep Learning based Recommendation.
An Online Intelligent Visual Interaction System.
Fair and Explainable Dynamic Engagement of Crowd Workers.
Multi-Agent Visualization for Explaining Federated Learning.
GraspSnooker: Automatic Chinese Commentary Generation for Snooker Videos.
Deep Reinforcement Learning for Ride-sharing Dispatching and Repositioning.
AiD-EM: Adaptive Decision Support for Electricity Markets Negotiations.
Reagent: Converting Ordinary Webpages into Interactive Software Agents.
SAGE: A Hybrid Geopolitical Event Forecasting System.
A Quantitative Analysis Platform for PD-L1 Immunohistochemistry based on Point-level Supervision Model.
ACTA A Tool for Argumentative Clinical Trial Analysis.
CRSRL: Customer Routing System Using Reinforcement Learning.
Mappa Mundi: An Interactive Artistic Mind Map Generator with Artificial Imagination.
CoTrRank: Trust Evaluation of Users and Tweets.
Neural Discourse Segmentation.
Design and Implementation of a Disambiguity Framework for Smart Voice Controlled Devices.
ERICA and WikiTalk.
The pywmi Framework and Toolbox for Probabilistic Inference using Weighted Model Integration.
Contextual Typeahead Sticker Suggestions on Hike Messenger.
DISPUTool - A tool for the Argumentative Analysis of Political Debates.
Agent-based Decision Support for Pain Management in Primary Care Settings.
The Open Vault Challenge - Learning How to Build Calibration-Free Interactive Systems by Cracking the Code of a Vault.
A Mobile Application for Sound Event Detection.
Embodied Conversational AI Agents in a Multi-modal Multi-agent Competitive Dialogue.
InterSpot: Interactive Spammer Detection in Social Media.
Demonstration of PerformanceNet: A Convolutional Neural Network Model for Score-to-Audio Music Generation.
VEST: A System for Vulnerability Exploit Scoring & Timing.
Crowd View: Converting Investors' Opinions into Indicators.
AntProphet: an Intention Mining System behind Alipay's Intelligent Customer Service Bot.
Hintikka's World: Scalable Higher-order Knowledge.
Multi-Agent Path Finding on Ozobots.
Explainable Deep Neural Networks for Multivariate Time Series Predictions.
OpenMarkov, an Open-Source Tool for Probabilistic Graphical Models.
Personal Context Recognition via Skeptical Learning.
Entity Alignment for Cross-lingual Knowledge Graph with Graph Convolutional Networks.
Evolutionary Learning of Existential Rules.
Self-Organizing Incremental Neural Networks for Continual Learning.
AI at the Margins: Data, Decisions, and Inclusive Social Impact.
Adversarial Machine Learning with Double Oracle.
A Compliance Checking Framework for DNN Models.
The Design of Human Oversight in Autonomous Weapon Systems.
Cautious Rule-Based Collective Inference.
Matching with Constraints.
Deep Learning with Relational Logic Representations.
Safe and Sample-Efficient Reinforcement Learning Algorithms for Factored Environments.
Intelligent Querying in Camera Networks for Efficient Target Tracking.
Preference Elicitation and Explanation in Iterative Planning.
Technical, Hard and Explainable Question Answering (THE-QA).
Towards Architecture-Agnostic Neural Transfer: a Knowledge-Enhanced Approach.
Event Prediction in Complex Social Graphs using One-Dimensional Convolutional Neural Network.
Split Q Learning: Reinforcement Learning with Two-Stream Rewards.
Optimizing Interactive Systems with Data-Driven Objectives.
Intelligent Agent for Assessing and Guiding Rehabilitation Exercises.
Unsupervised Multi-view Learning.
Can Meta-Interpretive Learning outperform Deep Reinforcement Learning of Evaluable Game strategies?.
A Unified Mathematical Approach for Foraging and Construction Systems in a 1, 000, 000 Robot Swarm.
Vision beyond Pixels: Visual Reasoning via Blocksworld Abstractions.
Teaching Robots to Interact with Humans in a Smart Environment.
Finding Justifications by Approximating Core for Large-scale Ontologies.
A Similarity Measurement Method Based on Graph Kernel for Disconnected Graphs.
AI in Recruiting. Multi-agent Systems Architecture for Ethical and Legal Auditing.
Visionary Security: Using Uncertain Real-Time Information in Signaling Games.
Constraint Solving and Optimization Using Evolutionary Techniques.
Conditional Preference Network with Constraints and Uncertainty.
What Does the Evidence Say? Models to Help Make Sense of the Biomedical Literature.
Domain-Dependent and Domain-Independent Problem Solving Techniques.
AI Planning for Enterprise: Putting Theory Into Practice.
From Data to Knowledge Engineering for Cybersecurity.
Multiagent Decision Making and Learning in Urban Environments.
Integrating Learning with Game Theory for Societal Challenges.
The Quest For "Always-On" Autonomous Mobile Robots.
On the Responsibility for Undecisiveness in Preferred and Stable Labellings in Abstract Argumentation (Extended Abstract).
Teaching AI Agents Ethical Values Using Reinforcement Learning and Policy Orchestration.
Implicitly Coordinated Multi-Agent Path Finding under Destination Uncertainty: Success Guarantees and Computational Complexity (Extended Abstract).
Shielded Base Contraction (Extended Abstract).
Complexity of Fundamental Problems in Probabilistic Abstract Argumentation: Beyond Independence (Extended Abstract).
A Core Method for the Weak Completion Semantics with Skeptical Abduction (Extended Abstract).
Complexity Bounds for the Controllability of Temporal Networks with Conditions, Disjunctions, and Uncertainty (Extended Abstract).
Learning in the Machine: Random Backpropagation and the Deep Learning Channel (Extended Abstract).
Leveraging Human Guidance for Deep Reinforcement Learning Tasks.
Sequential Recommender Systems: Challenges, Progress and Prospects.
Recent Advances in Imitation Learning from Observation.
Social Media-based User Embedding: A Literature Review.
A Survey of Reinforcement Learning Informed by Natural Language.
Automated Essay Scoring: A Survey of the State of the Art.
Learning and Inference for Structured Prediction: A Unifying Perspective.
Deep Learning for Video Captioning: A Review.
Counterfactuals in Explainable Artificial Intelligence (XAI): Evidence from Human Reasoning.
A Survey on Hierarchical Planning - One Abstract Idea, Many Concrete Realizations.
A Replication Study of Semantics in Argumentation.
Integrating Knowledge and Reasoning in Image Understanding.
Adversarial Attacks on Neural Networks for Graph Data.
Taskonomy: Disentangling Task Transfer Learning.
Causal Embeddings for Recommendation: An Extended Abstract.
Differentiable Physics and Stable Modes for Tool-Use and Manipulation Planning - Extended Abtract.
Trust Dynamics and Transfer across Human-Robot Interaction Tasks: Bayesian and Neural Computational Models.
Optimally Efficient Bidirectional Search.
Constraint Games for Stable and Optimal Allocation of Demands in SDN.
Not All FPRASs are Equal: Demystifying FPRASs for DNF-Counting (Extended Abstract).
Discovering Reliable Dependencies from Data: Hardness and Improved Algorithms.
Impact of Consuming Suggested Items on the Assessment of Recommendations in User Studies on Recommender Systems.
Delayed Impact of Fair Machine Learning.
A Walkthrough for the Principle of Logit Separation.
Meta-Interpretive Learning Using HEX-Programs.
On Causal Identification under Markov Equivalence.
The Power of Context in Networks: Ideal Point Models with Social Interactions.
On Guiding Search in HTN Planning with Classical Planning Heuristics.
Clause Learning and New Bounds for Graph Coloring.
The Provable Virtue of Laziness in Motion Planning.
A Dual Approach to Verify and Train Deep Networks.
Sharpness of the Satisfiability Threshold for Non-Uniform Random k-SAT.
Addressing Age-Related Bias in Sentiment Analysis.
Do We Need Many-valued Logics for Incomplete Information?.
Quality Control Attack Schemes in Crowdsourcing.
Closed-World Semantics for Conjunctive Queries with Negation over ELH-bottom Ontologies.
A Refined Understanding of Cost-optimal Planning with Polytree Causal Graphs.
Synthesizing Datalog Programs using Numerical Relaxation.
How Well Do Machines Perform on IQ tests: a Comparison Study on a Large-Scale Dataset.
EL Embeddings: Geometric Construction of Models for the Description Logic EL++.
Learning Hierarchical Symbolic Representations to Support Interactive Task Learning and Knowledge Transfer.
A Comparative Study of Distributional and Symbolic Paradigms for Relational Learning.
Learning Relational Representations with Auto-encoding Logic Programs.
Playgol: Learning Programs Through Play.
LTL and Beyond: Formal Languages for Reward Function Specification in Reinforcement Learning.
K-margin-based Residual-Convolution-Recurrent Neural Network for Atrial Fibrillation Detection.
Learning Interpretable Relational Structures of Hinge-loss Markov Random Fields.
A Decomposition Approach for Urban Anomaly Detection Across Spatiotemporal Data.
Balanced Ranking with Diversity Constraints.
Automatic Grassland Degradation Estimation Using Deep Learning.
Who Should Pay the Cost: A Game-theoretic Model for Government Subsidized Investments to Improve National Cybersecurity.
Protecting Neural Networks with Hierarchical Random Switching: Towards Better Robustness-Accuracy Trade-off for Stochastic Defenses.
Failure-Scenario Maker for Rule-Based Agent using Multi-agent Adversarial Reinforcement Learning and its Application to Autonomous Driving.
Group-Fairness in Influence Maximization.
Bidirectional Active Learning with Gold-Instance-Based Human Training.
Controllable Neural Story Plot Generation via Reward Shaping.
Simultaneous Prediction Intervals for Patient-Specific Survival Curves.
Daytime Sleepiness Level Prediction Using Respiratory Information.
Three-quarter Sibling Regression for Denoising Observational Data.
Pre-training of Graph Augmented Transformers for Medication Recommendation.
Global Robustness Evaluation of Deep Neural Networks with Provable Guarantees for the Hamming Distance.
MNN: Multimodal Attentional Neural Networks for Diagnosis Prediction.
KitcheNette: Predicting and Ranking Food Ingredient Pairings using Siamese Neural Network.
Diversity-Inducing Policy Gradient: Using Maximum Mean Discrepancy to Find a Set of Diverse Policies.
Scribble-to-Painting Transformation with Multi-Task Generative Adversarial Networks.
Truly Batch Apprenticeship Learning with Deep Successor Features.
Systematic Conservation Planning for Sustainable Land-use Policies: A Constrained Partitioning Approach to Reserve Selection and Design..
RDPD: Rich Data Helps Poor Data via Imitation.
MINA: Multilevel Knowledge-Guided Attention for Modeling Electrocardiography Signals.
CounterFactual Regression with Importance Sampling Weights.
mdfa: Multi-Differential Fairness Auditor for Black Box Classifiers.
Improving Customer Satisfaction in Bike Sharing Systems through Dynamic Repositioning.
DDL: Deep Dictionary Learning for Predictive Phenotyping.
Safe Contextual Bayesian Optimization for Sustainable Room Temperature PID Control Tuning.
Enhancing Stock Movement Prediction with Adversarial Training.
The Price of Local Fairness in Multistage Selection.
PI-Bully: Personalized Cyberbullying Detection with Peer Influence.
Risk Assessment for Networked-guarantee Loans Using High-order Graph Attention Representation.
Improving Law Enforcement Daily Deployment Through Machine Learning-Informed Optimization under Uncertainty.
AI-powered Posture Training: Application of Machine Learning in Sitting Posture Recognition Using the LifeChair Smart Cushion.
Evaluating the Interpretability of the Knowledge Compilation Map: Communicating Logical Statements Effectively.
Decision Making for Improving Maritime Traffic Safety Using Constraint Programming.
Governance by Glass-Box: Implementing Transparent Moral Bounds for AI Behaviour.
SparseSense: Human Activity Recognition from Highly Sparse Sensor Data-streams Using Set-based Neural Networks.
DiffChaser: Detecting Disagreements for Deep Neural Networks.
ISLF: Interest Shift and Latent Factors Combination Model for Session-based Recommendation.
Ranked Programming.
Cutset Bayesian Networks: A New Representation for Learning Rao-Blackwellised Graphical Models.
Hyper-parameter Tuning under a Budget Constraint.
Exact Bernoulli Scan Statistics using Binary Decision Diagrams.
An End-to-End Community Detection Model: Integrating LDA into Markov Random Field via Factor Graph.
On Constrained Open-World Probabilistic Databases.
Thompson Sampling on Symmetric Alpha-Stable Bandits.
Bayesian Parameter Estimation for Nonlinear Dynamics Using Sensitivity Analysis.
Lifted Message Passing for Hybrid Probabilistic Inference.
Statistical Guarantees for the Robustness of Bayesian Neural Networks.
Region Deformer Networks for Unsupervised Depth Estimation from Unconstrained Monocular Videos.
Unsupervised Learning of Monocular Depth and Ego-Motion using Conditional PatchGANs.
The Parameterized Complexity of Motion Planning for Snake-Like Robots.
Energy-Efficient Slithering Gait Exploration for a Snake-Like Robot Based on Reinforcement Learning.
Steady-State Policy Synthesis for Verifiable Control.
Merge-and-Shrink Task Reformulation for Classical Planning.
On Computational Complexity of Pickup-and-Delivery Problems with Precedence Constraints or Time Windows.
Scheduling Jobs with Stochastic Processing Time on Parallel Identical Machines.
Pattern Selection for Optimal Classical Planning with Saturated Cost Partitioning.
A Novel Distribution-Embedded Neural Network for Sensor-Based Activity Recognition.
Adaptive Thompson Sampling Stacks for Memory Bounded Open-Loop Planning.
Partitioning Techniques in LTLf Synthesis.
Bayesian Inference of Linear Temporal Logic Specifications for Contrastive Explanations.
Approximability of Constant-horizon Constrained POMDP.
Dynamic logic of parallel propositional assignments and its applications to planning.
Fair Online Allocation of Perishable Goods and its Application to Electric Vehicle Charging.
Subgoal-Based Temporal Abstraction in Monte-Carlo Tree Search.
Generalized Potential Heuristics for Classical Planning.
Online Probabilistic Goal Recognition over Nominal Models.
Influence of State-Variable Constraints on Partially Observable Monte Carlo Planning.
Counterexample-Guided Strategy Improvement for POMDPs Using Recurrent Neural Networks.
Strong Fully Observable Non-Deterministic Planning with LTL and LTLf Goals.
Regular Decision Processes: A Model for Non-Markovian Domains.
Faster Dynamic Controllability Checking in Temporal Networks with Integer Bounds.
Finding Optimal Solutions in HTN Planning - A SAT-based Approach.
Earliest-Completion Scheduling of Contract Algorithms with End Guarantees.
A Span-based Joint Model for Opinion Target Extraction and Target Sentiment Classification.
Getting in Shape: Word Embedding SubSpaces.
Sequence Generation: From Both Sides to the Middle.
Dynamically Route Hierarchical Structure Representation to Attentive Capsule for Text Classification.
RLTM: An Efficient Neural IR Framework for Long Documents.
Recurrent Neural Network for Text Classification with Hierarchical Multiscale Dense Connections.
A Document-grounded Matching Network for Response Selection in Retrieval-based Chatbots.
Quantum-Inspired Interactive Networks for Conversational Sentiment Analysis.
Multi-view Knowledge Graph Embedding for Entity Alignment.
Extracting Entities and Events as a Single Task Using a Transition-Based Neural Model.
Modeling both Context- and Speaker-Sensitive Dependence for Emotion Detection in Multi-speaker Conversations.
Adapting BERT for Target-Oriented Multimodal Sentiment Classification.
Beyond Word Attention: Using Segment Attention in Neural Relation Extraction.
Refining Word Representations by Manifold Learning.
Graph-based Neural Sentence Ordering.
Utilizing Non-Parallel Text for Style Transfer by Making Partial Comparisons.
Improving Multilingual Sentence Embedding using Bi-directional Dual Encoder with Additive Margin Softmax.
Triplet Enhanced AutoEncoder: Model-free Discriminative Network Embedding.
Knowledgeable Storyteller: A Commonsense-Driven Generative Model for Visual Storytelling.
Knowledge-enhanced Hierarchical Attention for Community Question Answering with Multi-task and Adaptive Learning.
HorNet: A Hierarchical Offshoot Recurrent Network for Improving Person Re-ID via Image Captioning.
Robust Audio Adversarial Example for a Physical Attack.
Neural Collective Entity Linking Based on Recurrent Random Walk Network Learning.
Polygon-Net: A General Framework for Jointly Boosting Multiple Unsupervised Neural Machine Translation Models.
Earlier Attention? Aspect-Aware LSTM for Aspect-Based Sentiment Analysis.
Dual-View Variational Autoencoders for Semi-Supervised Text Matching.
A Goal-Driven Tree-Structured Neural Model for Math Word Problems.
Sharing Attention Weights for Fast Transformer.
RTHN: A RNN-Transformer Hierarchical Network for Emotion Cause Extraction.
Relation-Aware Entity Alignment for Heterogeneous Knowledge Graphs.
Mask and Infill: Applying Masked Language Model for Sentiment Transfer.
Modeling Noisy Hierarchical Types in Fine-Grained Entity Typing: A Content-Based Weighting Approach.
Correct-and-Memorize: Learning to Translate from Interactive Revisions.
Revealing Semantic Structures of Texts: Multi-grained Framework for Automatic Mind-map Generation.
Robust Embedding with Multi-Level Structures for Link Prediction.
T-CVAE: Transformer-Based Conditioned Variational Autoencoder for Story Completion.
Swell-and-Shrink: Decomposing Image Captioning by Transformation and Summarization.
Unsupervised Embedding Enhancements of Knowledge Graphs using Textual Associations.
PRoFET: Predicting the Risk of Firms from Event Transcripts.
GANs for Semi-Supervised Opinion Spam Detection.
Cold-Start Aware Deep Memory Network for Multi-Entity Aspect-Based Sentiment Analysis.
Exploiting Persona Information for Diverse Generation of Conversational Responses.
Knowledge Aware Semantic Concept Expansion for Image-Text Matching.
A Deep Generative Model for Code Switched Text.
Aligning Learning Outcomes to Learning Resources: A Lexico-Semantic Spatial Approach.
Learn to Select via Hierarchical Gate Mechanism for Aspect-Based Sentiment Analysis.
Improving Cross-Domain Performance for Relation Extraction via Dependency Prediction and Information Flow Control.
Learning Task-Specific Representation for Novel Words in Sequence Labeling.
Aspect-Based Sentiment Classification with Attentive Neural Turing Machines.
Randomized Greedy Search for Structured Prediction: Amortized Inference and Learning.
Unsupervised Neural Aspect Extraction with Sememes.
A Dual Reinforcement Learning Framework for Unsupervised Text Style Transfer.
Building Personalized Simulator for Interactive Search.
Network Embedding with Dual Generation Tasks.
Exploring and Distilling Cross-Modal Information for Image Captioning.
Deep Mask Memory Network with Semantic Dependency and Context Moment for Aspect Level Sentiment Classification.
Learning to Select Knowledge for Response Generation in Dialog Systems.
Reading selectively via Binary Input Gated Recurrent Unit.
Self-attentive Biaffine Dependency Parsing.
Towards Discriminative Representation Learning for Speech Emotion Recognition.
Adversarial Transfer for Named Entity Boundary Detection with Pointer Networks.
Knowledge Base Question Answering with Topic Units.
Incorporating Structural Information for Better Coreference Resolution.
Representation Learning with Weighted Inner Product for Universal Approximation of General Similarities.
Relation Extraction Using Supervision from Topic Knowledge of Relation Labels.
Leap-LSTM: Enhancing Long Short-Term Memory for Text Categorization.
GSN: A Graph-Structured Network for Multi-Party Dialogues.
Answering Binary Causal Questions Through Large-Scale Text Mining: An Evaluation Using Cause-Effect Pairs from Human Experts.
AmazonQA: A Review-Based Question Answering Task.
Dual Visual Attention Network for Visual Dialog.
CNN-Based Chinese NER with Lexicon Rethinking.
Modeling Source Syntax and Semantics for Neural AMR Parsing.
Difficulty Controllable Generation of Reading Comprehension Questions.
End-to-End Multi-Perspective Matching for Entity Resolution.
Learning Assistance from an Adversarial Critic for Multi-Outputs Prediction.
Coreference Aware Representation Learning for Neural Named Entity Recognition.
Learning towards Abstractive Timeline Summarization.
From Words to Sentences: A Progressive Learning Approach for Zero-resource Machine Translation with Visual Pivots.
Sentiment-Controllable Chinese Poetry Generation.
Generating Multiple Diverse Responses with Multi-Mapping and Posterior Mapping Selection.
A Latent Variable Model for Learning Distributional Relation Vectors.
Multi-Domain Sentiment Classification Based on Domain-Aware Embedding and Attention.
Medical Concept Representation Learning from Multi-source Data.
Neural Program Induction for KBQA Without Gold Programs or Query Annotations.
Early Discovery of Emerging Entities in Microblogs.
Pivotal Relationship Identification: The K-Truss Minimization Problem.
K-Core Maximization: An Edge Addition Approach.
On Privacy Protection of Latent Dirichlet Allocation Model Training.
Data Poisoning Attack against Knowledge Graph Embedding.
Temporal Pyramid Pooling Convolutional Neural Network for Cover Song Identification.
Toward Efficient Navigation of Massive-Scale Geo-Textual Streams.
BAYHENN: Combining Bayesian Deep Learning and Homomorphic Encryption for Secure DNN Inference.
FABA: An Algorithm for Fast Aggregation against Byzantine Attacks in Distributed Neural Networks.
Adversarial Examples for Graph Data: Deep Insights into Attack and Defense.
Novel Collaborative Filtering Recommender Friendly to Privacy Protection.
Binarized Collaborative Filtering with Distilling Graph Convolutional Network.
Principal Component Analysis in the Local Differential Privacy Model.
Lower Bound of Locally Differentially Private Sparse Covariance Matrix Estimation.
Two-Stage Generative Models of Simulating Training Data at The Voxel Level for Large-Scale Microscopy Bioimage Segmentation.
A Privacy Preserving Collusion Secure DCOP Algorithm.
Equally-Guided Discriminative Hashing for Cross-modal Retrieval.
Demystifying the Combination of Dynamic Slicing and Spectrum-based Fault Localization.
Heterogeneous Gaussian Mechanism: Preserving Differential Privacy in Deep Learning with Provable Robustness.
Decidability of Model Checking Multi-Agent Systems with Regular Expressions against Epistemic HS Specifications.
LogAnomaly: Unsupervised Detection of Sequential and Quantitative Anomalies in Unstructured Logs.
Data Poisoning against Differentially-Private Learners: Attacks and Defenses.
Locate-Then-Detect: Real-time Web Attack Detection via Attention-based Deep Neural Networks.
Dilated Convolution with Dilated GRU for Music Source Separation.
Robustra: Training Provable Robust Neural Networks over Reference Adversarial Space.
Multiple Policy Value Monte Carlo Tree Search.
Musical Composition Style Transfer via Disentangled Timbre Representations.
Model-Agnostic Adversarial Detection by Random Perturbations.
Explainable Fashion Recommendation: A Semantic Attribute Region Guided Approach.
Real-Time Adversarial Attacks.
VulSniper: Focus Your Attention to Shoot Fine-Grained Vulnerabilities.
DeepInspect: A Black-box Trojan Detection and Mitigation Framework for Deep Neural Networks.
Procedural Generation of Initial States of Sokoban.
Predicting dominance in multi-person videos.
Disparity-preserved Deep Cross-platform Association for Cross-platform Video Recommendation.
Dual-Path in Dual-Path Network for Single Image Dehazing.
Learning Shared Vertex Representation in Heterogeneous Graphs with Convolutional Networks for Recommendation.
Medical Concept Embedding with Multiple Ontological Representations.
Node Embedding over Temporal Graphs.
Scaling Fine-grained Modularity Clustering for Massive Graphs.
Randomized Adversarial Imitation Learning for Autonomous Driving.
Faster Distributed Deep Net Training: Computation and Communication Decoupled Stochastic Gradient Descent.
FireCast: Leveraging Deep Learning to Predict Wildfire Spread.
Dynamic Electronic Toll Collection via Multi-Agent Deep Reinforcement Learning with Edge-Based Graph Convolutional Networks.
Representation Learning-Assisted Click-Through Rate Prediction.
Pseudo Supervised Matrix Factorization in Discriminative Subspace.
FSM: A Fast Similarity Measurement for Gene Regulatory Networks via Genes' Influence Power.
Playing Card-Based RTS Games with Deep Reinforcement Learning.
Hierarchical Graph Convolutional Networks for Semi-supervised Node Classification.
Combining ADMM and the Augmented Lagrangian Method for Efficiently Handling Many Constraints.
MLRDA: A Multi-Task Semi-Supervised Learning Framework for Drug-Drug Interaction Prediction.
A Quantum-inspired Classical Algorithm for Separable Non-negative Matrix Factorization.
Predicting the Visual Focus of Attention in Multi-Person Discussion Videos.
Exploiting the Sign of the Advantage Function to Learn Deterministic Policies in Continuous Domains.
Persistence Bag-of-Words for Topological Data Analysis.
Simultaneous Representation Learning and Clustering for Incomplete Multi-view Data.
Prediction of Mild Cognitive Impairment Conversion Using Auxiliary Information.
HDI-Forest: Highest Density Interval Regression Forest.
One-Shot Texture Retrieval with Global Context Metric.
Collaborative Metric Learning with Memory Network for Multi-Relational Recommender Systems.
Reinforcement Learning Experience Reuse with Policy Residual Representation.
Latent Distribution Preserving Deep Subspace Clustering.
BeatGAN: Anomalous Rhythm Detection using Adversarially Generated Time Series.
Metadata-driven Task Relation Discovery for Multi-task Learning.
AddGraph: Anomaly Detection in Dynamic Graph Using Attention-based Temporal GCN.
Large Scale Evolving Graphs with Burst Detection.
GAN-EM: GAN Based EM Learning Framework.
Multi-Prototype Networks for Unconstrained Set-based Face Recognition.
Localizing Unseen Activities in Video via Image Query.
Open-Ended Long-Form Video Question Answering via Hierarchical Convolutional Self-Attention Networks.
Scalable Block-Diagonal Locality-Constrained Projective Dictionary Learning.
ATTAIN: Attention-based Time-Aware LSTM Networks for Disease Progression Modeling.
DANE: Domain Adaptive Network Embedding.
Accelerated Inference Framework of Sparse Neural Network Based on Nested Bitmask Structure.
Taming the Noisy Gradient: Train Deep Neural Networks with Small Batch Sizes.
Multi-Group Encoder-Decoder Networks to Fuse Heterogeneous Data for Next-Day Air Quality Prediction.
InteractionNN: A Neural Network for Learning Hidden Features in Sparse Prediction.
Attributed Graph Clustering via Adaptive Graph Convolution.
Feature-level Deeper Self-Attention Network for Sequential Recommendation.
Quaternion Collaborative Filtering for Recommendation.
Inferring Substitutable Products with Deep Network Embedding.
Efficient Non-parametric Bayesian Hawkes Processes.
High Dimensional Bayesian Optimization via Supervised Dimension Reduction.
Towards Robust ResNet: A Small Step but a Giant Leap.
ProNE: Fast and Scalable Network Representation Learning.
Light-Weight Hybrid Convolutional Network for Liver Tumor Segmentation.
STAR-GCN: Stacked and Reconstructed Graph Convolutional Networks for Recommender Systems.
Generalized Majorization-Minimization for Non-Convex Optimization.
Positive and Unlabeled Learning with Label Disambiguation.
Experience Replay Optimization.
KCNN: Kernel-wise Quantization to Remarkably Decrease Multiplications in Convolutional Neural Network.
DARec: Deep Domain Adaptation for Cross-Domain Recommendation via Transferring Rating Patterns.
Progressive Transfer Learning for Person Re-identification.
Adaptive User Modeling with Long and Short-Term Preferences for Personalized Recommendation.
VAEGAN: A Collaborative Filtering Framework based on Adversarial Variational Autoencoders.
Interpreting and Evaluating Neural Network Robustness.
Semi-supervised Three-dimensional Reconstruction Framework with GAN.
Metatrace Actor-Critic: Online Step-Size Tuning by Meta-gradient Descent for Reinforcement Learning Control.
Belief Propagation Network for Hard Inductive Semi-Supervised Learning.
Geometric Understanding for Unsupervised Subspace Learning.
BN-invariant Sharpness Regularizes the Training Model to Better Generalization.
Neural Network based Continuous Conditional Random Field for Fine-grained Crime Prediction.
Out-of-sample Node Representation Learning for Heterogeneous Graph in Real-time Android Malware Detection.
Distributed Collaborative Feature Selection Based on Intermediate Representation.
A Vectorized Relational Graph Convolutional Network for Multi-Relational Network Alignment.
Amalgamating Filtered Knowledge: Learning Task-customized Student from Multi-task Teachers.
Multi-View Multiple Clustering.
Privacy-Preserving Stacking with Application to Cross-organizational Diabetes Prediction.
On the Estimation of Treatment Effect with Text Covariates.
SPAGAN: Shortest Path Graph Attention Network.
Comprehensive Semi-Supervised Multi-Modal Learning.
Legal Judgment Prediction via Multi-Perspective Bi-Feedback Network.
Deep Multi-Task Learning with Adversarial-and-Cooperative Nets.
Masked Graph Convolutional Network.
Dual Self-Paced Graph Convolutional Network: Towards Reducing Attribute Distortions Induced by Topology.
Topology Optimization based Graph Convolutional Network.
Low-Bit Quantization for Attributed Network Representation Learning.
Learning Strictly Orthogonal p-Order Nonnegative Laplacian Embedding via Smoothed Iterative Reweighted Method.
Multi-scale Information Diffusion Prediction with Reinforced Recurrent Networks.
Deep Correlated Predictive Subspace Learning for Incomplete Multi-View Semi-Supervised Classification.
Deep Spectral Kernel Learning.
Transfer of Temporal Logic Formulas in Reinforcement Learning.
On the Convergence of (Stochastic) Gradient Descent with Extrapolation for Non-Convex Minimization.
Zero-shot Metric Learning.
Learning Image-Specific Attributes by Hyperbolic Neighborhood Graph Propagation.
Latent Semantics Encoding for Label Distribution Learning.
Commit Message Generation for Source Code Changes.
MR-GNN: Multi-Resolution and Dual Graph Neural Network for Predicting Structured Entity Interactions.
Topology Attack and Defense for Graph Neural Networks: An Optimization Perspective.
Learning a Generative Model for Fusing Infrared and Visible Images via Conditional Generative Adversarial Network with Dual Discriminators.
Spatio-Temporal Attentive RNN for Node Classification in Temporal Attributed Graphs.
Graph Contextualized Self-Attention Network for Session-based Recommendation.
Adversarial Incomplete Multi-view Clustering.
CFM: Convolutional Factorization Machines for Context-Aware Recommendation.
Reparameterizable Subset Sampling via Continuous Relaxations.
Incremental Few-Shot Learning for Pedestrian Attribute Recognition.
BPAM: Recommendation Based on BP Neural Network with Attention Mechanism.
Graph Convolutional Networks on User Mobility Heterogeneous Graphs for Social Relationship Inference.
Trend-Aware Tensor Factorization for Job Skill Demand Analysis.
Multi-View Multi-Label Learning with View-Specific Information Extraction.
Feature Evolution Based Multi-Task Learning for Collaborative Filtering with Social Trust.
PD-GAN: Adversarial Learning for Personalized Diversity-Promoting Recommendation.
Neural News Recommendation with Attentive Multi-View Learning.
RobustTrend: A Huber Loss with a Combined First and Second Order Difference Regularization for Time Series Trend Filtering.
Bayesian Uncertainty Matching for Unsupervised Domain Adaptation.
Learning for Tail Label Data: A Label-Specific Feature Approach.
Learning Multi-Objective Rewards and User Utility Function in Contextual Bandits for Personalized Ranking.
Hierarchical Diffusion Attention Network.
Interactive Reinforcement Learning with Dynamic Reuse of Prior Knowledge from Human and Agent Demonstrations.
Unified Embedding Model over Heterogeneous Information Network for Personalized Recommendation.
Weak Supervision Enhanced Generative Network for Question Generation.
Tag2Gauss: Learning Tag Representations via Gaussian Distribution in Tagged Networks.
Position Focused Attention Network for Image-Text Matching.
COP: Customized Deep Model Compression via Regularized Correlation-Based Filter-Level Pruning.
Multi-view Clustering via Late Fusion Alignment Maximization.
Modeling Multi-Purpose Sessions for Next-Item Recommendations via Mixture-Channel Purpose Routing Networks.
Heterogeneous Graph Matching Networks for Unknown Malware Detection.
Partial Label Learning with Unlabeled Data.
MUSICAL: Multi-Scale Image Contextual Attention Learning for Inpainting.
Differentially Private Iterative Gradient Hard Thresholding for Sparse Learning.
Discrete Binary Coding based Label Distribution Learning.
Deep Cascade Generation on Point Sets.
Attributed Subspace Clustering.
Classification with Label Distribution Learning.
CLVSA: A Convolutional LSTM Based Variational Sequence-to-Sequence Model with Attention for Predicting Trends of Financial Markets.
DMRAN: A Hierarchical Fine-Grained Attention-Based Network for Recommendation.
Discriminative and Correlative Partial Multi-Label Learning.
Measuring Structural Similarities in Finite MDPs.
Spectral Perturbation Meets Incomplete Multi-view Data.
Attributed Graph Clustering: A Deep Attentional Embedding Approach.
Boundary Perception Guidance: A Scribble-Supervised Semantic Segmentation Approach.
Recurrent Existence Determination Through Policy Optimization.
Planning with Expectation Models.
Sharing Experience in Multitask Reinforcement Learning.
Interpolation Consistency Training for Semi-supervised Learning.
DeepCU: Integrating both Common and Unique Latent Information for Multimodal Sentiment Analysis.
Learning to Interpret Satellite Images using Wikipedia.
Ensemble-based Ultrahigh-dimensional Variable Screening.
Object Detection based Deep Unsupervised Hashing.
Deeper Connections between Neural Networks and Gaussian Processes Speed-up Active Learning.
Exchangeability and Kernel Invariance in Trained MLPs.
Imitation Learning from Video by Leveraging Proprioception.
Image Captioning with Compositional Neural Module Networks.
Hierarchical Inter-Attention Network for Document Classification with Multi-Task Learning.
Adversarial Graph Embedding for Ensemble Clustering.
AugBoost: Gradient Boosting Enhanced with Step-Wise Feature Augmentation.
Deeply-learned Hybrid Representations for Facial Age Estimation.
HMLasso: Lasso with High Missing Rate.
Metric Learning on Healthcare Data with Incomplete Modalities.
MEGAN: A Generative Adversarial Network for Multi-View Network Embedding.
Heavy-ball Algorithms Always Escape Saddle Points.
Adversarial Imitation Learning from Incomplete Demonstrations.
Multiplicative Sparse Feature Decomposition for Efficient Multi-View Multi-Task Learning.
Fast and Robust Multi-View Multi-Task Learning via Group Sparsity.
Finding Statistically Significant Interactions between Continuous Features.
Parallel Wasserstein Generative Adversarial Nets with Multiple Discriminators.
Playing FPS Games With Environment-Aware Hierarchical Reinforcement Learning.
Solving Continual Combinatorial Selection via Deep Reinforcement Learning.
Play and Prune: Adaptive Filter Pruning for Deep Model Compression.
Structure Learning for Safe Policy Improvement.
A Principled Approach for Learning Task Similarity in Multitask Learning.
The Pupil Has Become the Master: Teacher-Student Model-Based Word Embedding Distillation with Ensemble Learning.
Gradient Boosting with Piece-Wise Linear Regression Trees.
Soft Policy Gradient Method for Maximum Entropy Deep Reinforcement Learning.
Quadruply Stochastic Gradients for Large Scale Nonlinear Semi-Supervised AUC Optimization.
A Convergence Analysis of Distributed SGD with Communication-Efficient Gradient Sparsification.
Rapid Performance Gain through Active Model Reuse.
A Part Power Set Model for Scale-Free Person Retrieval.
On the Effectiveness of Low Frequency Perturbations.
Community Detection and Link Prediction via Cluster-driven Low-rank Matrix Completion.
Weakly Supervised Multi-task Learning for Semantic Parsing.
SynthNet: Learning to Synthesize Music End-to-End.
Deterministic Routing between Layout Abstractions for Multi-Scale Classification of Visually Rich Documents.
A Degeneracy Framework for Scalable Graph Autoencoders.
Discovering Regularities from Traditional Chinese Medicine Prescriptions via Bipartite Embedding Model.
Complementary Learning for Overcoming Catastrophic Forgetting Using Experience Replay.
Closed-Loop Memory GAN for Continual Learning.
Label Distribution Learning with Label Correlations via Low-Rank Approximation.
Label distribution learning with label-specific features.
Unifying the Stochastic and the Adversarial Bandits with Knapsack.
Successor Options: An Option Discovery Framework for Reinforcement Learning.
Automated Machine Learning with Monte-Carlo Tree Search.
Fairwalk: Towards Fair Graph Embedding.
Noise-Resilient Similarity Preserving Network Embedding for Social Networks.
Scalable Bayesian Non-linear Matrix Completion.
Improving representation learning in autoencoders via multidimensional interpolation and dual regularizations.
An Atari Model Zoo for Analyzing, Visualizing, and Comparing Deep Reinforcement Learning Agents.
Graph Space Embedding.
A Practical Semi-Parametric Contextual Bandit.
Fine-grained Event Categorization with Heterogeneous Graph Convolutional Networks.
Improving Cross-lingual Entity Alignment via Optimal Transport.
Exploiting Interaction Links for Node Classification with Deep Graph Neural Networks.
Indirect Trust is Simple to Establish.
Hill Climbing on Value Estimates for Search-control in Dyna.
Group LASSO with Asymmetric Structure Estimation for Multi-Task Learning.
Incremental Learning of Planning Actions in Model-Based Reinforcement Learning.
Outlier-Robust Multi-Aspect Streaming Tensor Completion and Factorization.
DyAt Nets: Dynamic Attention Networks for State Forecasting in Cyber-Physical Systems.
Deep Variational Koopman Models: Inferring Koopman Observations for Uncertainty-Aware Dynamics Modeling and Control.
Advantage Amplification in Slowly Evolving Latent-State Environments.
Robust Flexible Feature Selection via Exclusive L21 Regularization.
Meta-Learning for Low-resource Natural Language Generation in Task-oriented Dialogue Systems.
Unsupervised Hierarchical Temporal Abstraction by Simultaneously Learning Expectations and Representations.
Anytime Bottom-Up Rule Learning for Knowledge Graph Completion.
On Principled Entropy Exploration in Policy Optimization.
Coarse-to-Fine Image Inpainting via Region-wise Convolutions and Non-Local Correlation.
Monte Carlo Tree Search for Policy Optimization.
AttnSense: Multi-level Attention Mechanism For Multimodal Human Activity Recognition.
Weakly Supervised Multi-Label Learning via Label Enhancement.
E²GAN: End-to-End Generative Adversarial Network for Multivariate Time Series Imputation.
Knowledge Amalgamation from Heterogeneous Networks by Common Feature Learning.
Multi-Objective Generalized Linear Bandits.
Parametric Manifold Learning of Gaussian Mixture Models.
Learning Low-precision Neural Networks without Straight-Through Estimator (STE).
Hi-Fi Ark: Deep User Representation via High-Fidelity Archive Network.
Omnidirectional Scene Text Detection with Sequential-free Box Discretization.
Accelerated Incremental Gradient Descent using Momentum Acceleration with Scaling Factor.
Graph and Autoencoder Based Feature Extraction for Zero-shot Learning.
Supervised Short-Length Hashing.
Margin Learning Embedded Prediction for Video Anomaly Detection with A Few Anomalies.
Prototype Propagation Networks (PPN) for Weakly-supervised Few-shot Learning on Category Graph.
Learning Robust Distance Metric with Side Information via Ratio Minimization of Orthogonally Constrained L21-Norm Distances.
Learning Instance-wise Sparsity for Accelerating Deep Models.
Feature Prioritization and Regularization Improve Standard Accuracy and Adversarial Robustness.
Balanced Clustering: A Uniform Model and Fast Algorithm.
Image-to-Image Translation with Multi-Path Consistency Regularization.
Worst-Case Discriminative Feature Selection.
Learning K-way D-dimensional Discrete Embedding for Hierarchical Data Visualization and Retrieval.
GCN-LASE: Towards Adequately Incorporating Link Attributes in Graph Convolutional Networks.
Deep Adversarial Multi-view Clustering Network.
ARMIN: Towards a More Efficient and Light-weight Recurrent Memory Network.
Learning Network Embedding with Community Structural Information.
Linear Time Complexity Time Series Clustering with Symbolic Pattern Forest.
Improved Algorithm on Online Clustering of Bandits.
Flexible Multi-View Representation Learning for Subspace Clustering.
Improving the Robustness of Deep Neural Networks via Adversarial Training with Triplet Loss.
Learning Interpretable Deep State Space Model for Probabilistic Time Series Forecasting.
Dense Transformer Networks for Brain Electron Microscopy Image Segmentation.
Approximate Manifold Regularization: Scalable Algorithm and Generalization Analysis.
Multi-Class Learning using Unlabeled Samples: Theory and Algorithm.
Hierarchical Representation Learning for Bipartite Graphs.
A Review-Driven Neural Model for Sequential Recommendation.
Cascading Non-Stationary Bandits: Online Learning to Rank in the Non-Stationary Cascade Model.
Differentially Private Optimal Transport: Application to Domain Adaptation.
Similarity Preserving Representation Learning for Time Series Clustering.
Learning Shared Knowledge for Deep Lifelong Learning using Deconvolutional Networks.
Action Space Learning for Heterogeneous User Behavior Prediction.
Learning Generative Adversarial Networks from Multiple Data Sources.
Learning Multiple Maps from Conditional Ordinal Triplets.
Correlation-Sensitive Next-Basket Recommendation.
The Dangers of Post-hoc Interpretability: Unjustified Counterfactual Explanations.
Meta Reinforcement Learning with Task Embedding and Shared Policy.
Perturbed-History Exploration in Stochastic Multi-Armed Bandits.
Harnessing the Vulnerability of Latent Layers in Adversarially Trained Models.
Learning Sound Events from Webly Labeled Data.
Adaptive Ensemble Active Learning for Drifting Data Stream Mining.
Autoregressive Policies for Continuous Control Deep Reinforcement Learning.
Single-Channel Signal Separation and Deconvolution with Generative Adversarial Networks.
Sequential and Diverse Recommendation with Long Tail.
DeepMellow: Removing the Need for a Target Network in Deep Q-Learning.
Outlier Detection for Time Series with Recurrent Autoencoder Ensembles.
What to Expect of Classifiers? Reasoning about Logistic Regression with Missing Features.
Twin-Systems to Explain Artificial Neural Networks using Case-Based Reasoning: Comparative Tests of Feature-Weighting Methods in ANN-CBR Twins for XAI.
Multiple Partitions Aligned Clustering.
Interactive Teaching Algorithms for Inverse Reinforcement Learning.
Obstacle Tower: A Generalization Challenge in Vision, Control, and Planning.
Submodular Batch Selection for Training Deep Neural Networks.
Hypergraph Induced Convolutional Manifold Networks.
Network-Specific Variational Auto-Encoder for Embedding in Attribute Networks.
CensNet: Convolution with Edge-Node Switching in Graph Neural Networks.
Robust Low-Tubal-Rank Tensor Completion via Convex Optimization.
Convolutional Gaussian Embeddings for Personalized Recommendation with Uncertainty.
Dynamic Hypergraph Neural Networks.
Recurrent Generative Networks for Multi-Resolution Satellite Data: An Application in Cropland Monitoring.
Patent Citation Dynamics Modeling via Multi-Attention Recurrent Networks.
Learning to Learn Gradient Aggregation by Gradient Descent.
Assumed Density Filtering Q-learning.
Accelerating Extreme Classification via Adaptive Feature Agglomeration.
SlateQ: A Tractable Decomposition for Reinforcement Learning with Recommendation Sets.
Efficient Protocol for Collaborative Dictionary Learning in Decentralized Networks.
Entangled Kernels.
Conditions on Features for Temporal Difference-Like Methods to Converge.
Multi-view Spectral Clustering Network.
Nostalgic Adam: Weighting More of the Past Gradients When Designing the Adaptive Learning Rate.
Zeroth-Order Stochastic Alternating Direction Method of Multipliers for Nonconvex Nonsmooth Optimization.
Privacy-aware Synthesizing for Crowdsourced Data.
Deep Metric Learning: The Generalization Analysis and an Adaptive Algorithm.
Cascaded Algorithm-Selection and Hyper-Parameter Optimization with Extreme-Region Upper Confidence Bound Bandit.
Hybrid Item-Item Recommendation via Semi-Parametric Embedding.
Robust Learning from Noisy Side-information by Semidefinite Programming.
Group-based Learning of Disentangled Representations with Generalizability for Novel Contents.
Learning Topic Models by Neighborhood Aggregation.
Online Learning from Capricious Data Streams: A Generative Approach.
Deliberation Learning for Image-to-Image Translation.
One Network for Multi-Domains: Domain Adaptive Hashing with Intersectant Generative Adversarial Networks.
Deep Active Learning with Adaptive Acquisition.
Network Embedding under Partial Monitoring for Evolving Networks.
Attribute Aware Pooling for Pedestrian Attribute Recognition.
Confirmatory Bayesian Online Change Point Detection in the Covariance Structure of Gaussian Processes.
MineRL: A Large-Scale Dataset of Minecraft Demonstrations.
Landmark Selection for Zero-shot Learning.
Zero-shot Learning with Many Classes by High-rank Deep Embedding Networks.
AdaLinUCB: Opportunistic Learning for Contextual Bandits.
Affine Equivariant Autoencoder.
Discriminative Sample Generation for Deep Imbalanced Learning.
SPINE: Structural Identity Preserved Inductive Network Embedding.
Sketched Iterative Algorithms for Structured Generalized Linear Models.
Using Natural Language for Reward Shaping in Reinforcement Learning.
Efficient Regularization Parameter Selection for Latent Variable Graphical Models via Bi-Level Optimization.
Perception-Aware Point-Based Value Iteration for Partially Observable Markov Decision Processes.
Scalable Semi-Supervised SVM via Triply Stochastic Gradients.
Fully Distributed Bayesian Optimization with Stochastic Policies.
Reward Learning for Efficient Reinforcement Learning in Extractive Document Summarisation.
RecoNet: An Interpretable Neural Architecture for Recommender Systems.
Automatic Successive Reinforcement Learning with Multiple Auxiliary Rewards.
Deep Multi-Agent Reinforcement Learning with Discrete-Continuous Hybrid Action Spaces.
Neurons Merging Layer: Towards Progressive Redundancy Reduction for Deep Supervised Hashing.
Advocacy Learning: Learning through Competition and Class-Conditional Representations.
Curriculum Learning for Cumulative Return Maximization.
Deep Session Interest Network for Click-Through Rate Prediction.
Partial Label Learning by Semantic Difference Maximization.
GSTNet: Global Spatial-Temporal Network for Traffic Flow Prediction.
Hybrid Actor-Critic Reinforcement Learning in Parameterized Action Space.
iDev: Enhancing Social Coding Security by Cross-platform User Identification Between GitHub and Stack Overflow.
Mindful Active Learning.
Fast Algorithm for K-Truss Discovery on Public-Private Graphs.
Joint Link Prediction and Network Alignment via Cross-graph Embedding.
Crafting Efficient Neural Graph of Large Entropy.
Group Reconstruction and Max-Pooling Residual Capsule Network.
Reinforced Negative Sampling for Recommendation with Exposure Data.
Marginal Posterior Sampling for Slate Bandits.
IRC-GAN: Introspective Recurrent Convolutional GAN for Text-to-video Generation.
Learn Smart with Less: Building Better Online Decision Trees with Fewer Training Examples.
Three-Player Wasserstein GAN via Amortised Duality.
Recommending Links to Maximize the Influence in Social Networks.
Extrapolating Paths with Graph Neural Networks.
A Strongly Asymptotically Optimal Agent in General Environments.
Ornstein Auto-Encoders.
Approximate Optimal Transport for Continuous Densities with Copulas.
Success Prediction on Crowdfunding with Multimodal Deep Learning.
Deep Active Learning for Anchor User Prediction.
Variational Graph Embedding and Clustering with Laplacian Eigenmaps.
Co-Attentive Multi-Task Learning for Explainable Recommendation.
A Restart-based Rank-1 Evolution Strategy for Reinforcement Learning.
ActiveHNE: Active Heterogeneous Network Embedding.
Semi-supervised User Profiling with Heterogeneous Graph Attention Networks.
Extensible Cross-Modal Hashing.
Cooperative Pruning in Cross-Domain Deep Neural Network Compression.
Matching User with Item Set: Collaborative Bundle Recommendation with Deep Attention Network.
Learning Semantic Annotations for Tabular Data.
Theoretical Investigation of Generalization Bound for Residual Networks.
FakeTables: Using GANs to Generate Functional Dependency Preserving Tables with Bounded Real Data.
Tree Sampling Divergence: An Information-Theoretic Metric for Hierarchical Graph Clustering.
Learning Disentangled Semantic Representation for Domain Adaptation.
Multi-View Active Learning for Video Recommendation.
Active Learning within Constrained Environments through Imitation of an Expert Questioner.
Matrix Completion in the Unit Hypercube via Structured Matrix Factorization.
A Gradient-Based Split Criterion for Highly Accurate and Transparent Model Trees.
Incremental Elicitation of Rank-Dependent Aggregation Functions based on Bayesian Linear Regression.
Optimal Exploitation of Clustering and History Information in Multi-armed Bandit.
Motion Invariance in Visual Environments.
An Actor-Critic-Attention Mechanism for Deep Reinforcement Learning in Multi-view Environments.
Conditional GAN with Discriminative Filter Generation for Text-to-Video Synthesis.
Unsupervised Inductive Graph-Level Representation Learning via Graph-Graph Proximity.
STG2Seq: Spatial-Temporal Graph to Sequence Model for Multi-step Passenger Demand Forecasting.
Unobserved Is Not Equal to Non-existent: Using Gaussian Processes to Infer Immediate Rewards Across Contexts.
Inter-node Hellinger Distance based Decision Tree.
Human-in-the-loop Active Covariance Learning for Improving Prediction in Small Data Sets.
The Expected-Length Model of Options.
Neighborhood-Aware Attentional Representation for Multilingual Knowledge Graphs.
TransMS: Knowledge Graph Embedding for Complex Relations by Multidirectional Semantics.
Graph Convolutional Networks using Heat Kernel for Semi-supervised Learning.
Boosting Causal Embeddings via Potential Verb-Mediated Causal Patterns.
Profit-driven Task Assignment in Spatial Crowdsourcing.
Graph WaveNet for Deep Spatial-Temporal Graph Modeling.
A Modal Characterization Theorem for a Probabilistic Fuzzy Description Logic.
Cross-City Transfer Learning for Deep Spatio-Temporal Prediction.
DatalogMTL: Computational Complexity and Expressive Power.
Out of Sight But Not Out of Mind: An Answer Set Programming Based Online Abduction Framework for Visual Sensemaking in Autonomous Driving.
Estimating Causal Effects of Tone in Online Debates.
What Has Been Said? Identifying the Change Formula in a Belief Revision Scenario.
Belief Update without Compactness in Non-finitary Languages.
Data Complexity and Rewritability of Ontology-Mediated Queries in Metric Temporal Logic under the Event-Based Semantics.
Boosting for Comparison-Based Learning.
Monitoring of a Dynamic System Based on Autoencoders.
Satisfaction and Implication of Integrity Constraints in Ontology-based Data Access.
BiOWA for Preference Aggregation with Bipolar Scales: Application to Fair Optimization in Combinatorial Domains.
Automatic Verification of FSA Strategies via Counterexample-Guided Local Search for Invariants.
Geo-ALM: POI Recommendation by Fusing Geographical Information and Adversarial Learning Mechanism.
Story Ending Prediction by Transferable BERT.
Unit Selection Based on Counterfactual Logic.
Revisiting Controlled Query Evaluation in Description Logics.
Augmenting Transfer Learning with Semantic Reasoning.
Travel Time Estimation without Road Networks: An Urban Morphological Layout Representation Approach.
A Tractable, Expressive, and Eventually Complete First-Order Logic of Limited Belief.
How to Handle Missing Values in Multi-Criteria Decision Aiding?.
Rational Inference Relations from Maximal Consistent Subsets Selection.
Converging on Common Knowledge.
Some Things are Easier for the Dumb and the Bright Ones (Beware the Average!).
Belief Revision Operators with Varying Attitudes Towards Initial Beliefs.
On Finite and Unrestricted Query Entailment beyond SQ with Number Restrictions on Transitive Roles.
On Division Versus Saturation in Pseudo-Boolean Solving.
Best Answers over Incomplete Data : Complexity and First-Order Rewritings.
Approximating Integer Solution Counting via Space Quantification for Linear Constraints.
Aggressive Driving Saves More Time? Multi-task Learning for Customized Travel Time Estimation.
Learning Description Logic Concepts: When can Positive and Negative Examples be Separated?.
An ASP Approach to Generate Minimal Countermodels in Intuitionistic Propositional Logic.
Answer Set Programming for Judgment Aggregation.
From Statistical Transportability to Estimating the Effect of Stochastic Interventions.
Measuring the Likelihood of Numerical Constraints.
Semantic Characterization of Data Services through Ontologies.
Explanations for Query Answers under Existential Rules.
Simple Conditionals with Constrained Right Weakening.
Chasing Sets: How to Use Existential Rules for Expressive Reasoning.
Enriching Ontology-based Data Access with Provenance.
Causal Discovery with Cascade Nonlinear Additive Noise Model.
Planning for LTLf /LDLf Goals in Non-Markovian Fully Observable Nondeterministic Domains.
The Complexity of Model Checking Knowledge and Time.
Reasoning about Quality and Fuzziness of Strategic Behaviours.
Oblivious and Semi-Oblivious Boundedness for Existential Rules.
Ontology Approximation in Horn Description Logics.
Guarantees for Sound Abstractions for Generalized Planning.
Mixed-World Reasoning with Existential Rules under Active-Domain Semantics.
Reasoning about Disclosure in Data Integration in the Presence of Source Constraints.
Possibilistic Games with Incomplete Information.
Comparing Options with Argument Schemes Powered by Cancellation.
Worst-Case Optimal Querying of Very Expressive Description Logics with Path Expressions and Succinct Counting.
Stratified Evidence Logics.
Do You Need Infinite Time?.
Observations on Darwiche and Pearl's Approach for Iterated Belief Revision.
Compilation of Logical Arguments.
On the Integration of CP-nets in ASPRIN.
ASP-based Discovery of Semi-Markovian Causal Models under Weaker Assumptions.
FAHT: An Adaptive Fairness-aware Decision Tree Classifier.
Multiple Noisy Label Distribution Propagation for Crowdsourcing.
An Input-aware Factorization Machine for Sparse Prediction.
DeepAPF: Deep Attentive Probabilistic Factorization for Multi-site Video Recommendation.
Achieving Causal Fairness through Generative Adversarial Networks.
Fast and Accurate Classification with a Multi-Spike Learning Algorithm for Spiking Neurons.
Counterfactual Fairness: Unidentification, Bound and Algorithm.
Personalized Multimedia Item and Key Frame Recommendation.
Why Can't You Do That HAL? Explaining Unsolvability of Planning Tasks.
DeepFlow: Detecting Optimal User Experience From Physiological Data Using Deep Neural Networks.
Minimizing Time-to-Rank: A Learning and Recommendation Approach.
Exploring Computational User Models for Agent Policy Summarization.
MiSC: Mixed Strategies Crowdsourcing.
Decoding EEG by Visual-guided Deep Neural Networks.
Discrete Trust-aware Matrix Factorization for Fast Recommendation.
Dynamic Item Block and Prediction Enhancing Block for Sequential Recommendation.
STCA: Spatio-Temporal Credit Assignment with Delayed Feedback in Deep Spiking Neural Networks.
A Semantics-based Model for Predicting Children's Vocabulary.
Deep Adversarial Social Recommendation.
Multi-agent Attentional Activity Recognition.
Balancing Explicability and Explanations in Human-Aware Planning.
Explaining Reinforcement Learning to Mere Mortals: An Empirical Study.
Non-smooth Optimization over Stiefel Manifolds with Applications to Dimensionality Reduction and Graph Clustering.
Heuristic Search for Homology Localization Problem and Its Application in Cardiac Trabeculae Reconstruction.
Learning Deep Decentralized Policy Network by Collective Rewards for Real-Time Combat Game.
Local Search with Efficient Automatic Configuration for Minimum Vertex Cover.
Branch-and-Cut-and-Price for Multi-Agent Pathfinding.
Depth-First Memory-Limited AND/OR Search and Unsolvability in Cyclic Search Spaces.
Graph Mining Meets Crowdsourcing: Extracting Experts for Answer Aggregation.
DeltaDou: Expert-level Doudizhu AI through Self-play.
Direction-Optimizing Breadth-First Search with External Memory Storage.
Iterative Budgeted Exponential Search.
Regarding Jump Point Search and Subgoal Graphs.
An Evolution Strategy with Progressive Episode Lengths for Playing Games.
An Efficient Evolutionary Algorithm for Minimum Cost Submodular Cover.
Conditions for Avoiding Node Re-expansions in Bounded Suboptimal Search.
Deanonymizing Social Networks Using Structural Information.
A*+IDA*: A Simple Hybrid Search Algorithm.
Path Planning with CPD Heuristics.
Resolution and Domination: An Improved Exact MaxSAT Algorithm.
Integrating Pseudo-Boolean Constraint Reasoning in Multi-Objective Evolutionary Algorithms.
Unifying Search-based and Compilation-based Approaches to Multi-agent Path Finding through Satisfiability Modulo Theories.
GANAK: A Scalable Probabilistic Exact Model Counter.
Phase Transition Behavior of Cardinality and XOR Constraints.
Constraint-Based Scheduling with Complex Setup Operations: An Iterative Two-Layer Approach.
Optimizing Constraint Solving via Dynamic Programming.
Stochastic Constraint Propagation for Mining Probabilistic Networks.
Acquiring Integer Programs from Data.
Entropy-Penalized Semidefinite Programming.
Enumerating Potential Maximal Cliques via SAT and ASP.
Model-Based Diagnosis with Multiple Observations.
DoubleLex Revisited and Beyond.
Solving the Satisfiability Problem of Modal Logic S5 Guided by Graph Coloring.
Privacy-Preserving Obfuscation of Critical Infrastructure Networks.
Predict+Optimise with Ranking Objectives: Exhaustively Learning Linear Functions.
How to Tame Your Anticipatory Algorithm.
Constraint Programming for Mining Borders of Frequent Itemsets.
Athanor: High-Level Local Search Over Abstract Constraint Specifications in Essence.
Face Photo-Sketch Synthesis via Knowledge Transfer.
LRDNN: Local-refining based Deep Neural Network for Person Re-Identification with Attribute Discerning.
Binarized Neural Networks for Resource-Efficient Hashing with Minimizing Quantization Loss.
Generative Visual Dialogue System via Weighted Likelihood Estimation.
Pose-preserving Cross Spectral Face Hallucination.
Capturing Spatial and Temporal Patterns for Facial Landmark Tracking through Adversarial Learning.
High Performance Gesture Recognition via Effective and Efficient Temporal Modeling.
Dynamically Visual Disambiguation of Keyword-based Image Search.
MSR: Multi-Scale Shape Regression for Scene Text Detection.
Graph Convolutional Network Hashing for Cross-Modal Retrieval.
Densely Supervised Hierarchical Policy-Value Network for Image Paragraph Generation.
Mutually Reinforced Spatio-Temporal Convolutional Tube for Human Action Recognition.
Video Interactive Captioning with Human Prompts.
Transferable Adversarial Attacks for Image and Video Object Detection.
DSRN: A Deep Scale Relationship Network for Scene Text Detection.
Convolutional Auto-encoding of Sentence Topics for Image Paragraph Generation.
Color-Sensitive Person Re-Identification.
Hallucinating Optical Flow Features for Video Classification.
Talking Face Generation by Conditional Recurrent Adversarial Network.
Deep Recurrent Quantization for Generating Sequential Binary Codes.
Deep Light-field-driven Saliency Detection from a Single View.
DBDNet: Learning Bi-directional Dynamics for Early Action Prediction.
Low Shot Box Correction for Weakly Supervised Object Detection.
Resolution-invariant Person Re-Identification.
Unsupervised Learning of Scene Flow Estimation Fusing with Local Rigidity.
Densely Connected Attention Flow for Visual Question Answering.
Nuclei Segmentation via a Deep Panoptic Model with Semantic Feature Fusion.
Rectified Binary Convolutional Networks for Enhancing the Performance of 1-bit DCNNs.
Attribute-Aware Convolutional Neural Networks for Facial Beauty Prediction.
Rethinking Loss Design for Large-scale 3D Shape Retrieval.
Pedestrian Attribute Recognition by Joint Visual-semantic Reasoning and Knowledge Distillation.
Variation Generalized Feature Learning via Intra-view Variation Adaptation.
Detecting Robust Co-Saliency with Recurrent Co-Attention Neural Network.
Generative Image Inpainting with Submanifold Alignment.
Supervised Set-to-Set Hashing in Visual Recognition.
Learning Unsupervised Visual Grounding Through Semantic Self-Supervision.
Multi-Level Visual-Semantic Alignments with Relation-Wise Dual Attention Network for Image and Text Matching.
Dynamic Feature Fusion for Semantic Edge Detection.
MAT-Net: Medial Axis Transform Network for 3D Object Recognition.
Parts4Feature: Learning 3D Global Features from Generally Semantic Parts in Multiple Views.
3DViewGraph: Learning Global Features for 3D Shapes from A Graph of Unordered Views with Attention.
Connectionist Temporal Modeling of Video and Language: a Joint Model for Translation and Sign Labeling.
Dense Temporal Convolution Network for Sign Language Translation.
Asynchronous Stochastic Frank-Wolfe Algorithms for Non-Convex Optimization.
ANODE: Unconditionally Accurate Memory-Efficient Gradients for Neural ODEs.
Beyond Product Quantization: Deep Progressive Quantization for Image Retrieval.
Learning to Draw Text in Natural Images with Conditional Adversarial Networks.
On Retrospecting Human Dynamics with Attention.
A Deep Bi-directional Attention Network for Human Motion Recovery.
Structure-Aware Residual Pyramid Network for Monocular Depth Estimation.
Generalized Zero-Shot Vehicle Detection in Remote Sensing Imagery via Coarse-to-Fine Framework.
Multi-Margin based Decorrelation Learning for Heterogeneous Face Recognition.
CoSegNet: Image Co-segmentation using a Conditional Siamese Convolutional Network.
Explore Truthful Incentives for Tasks with Heterogenous Levels of Difficulty in the Sharing Economy.
Decentralized Optimization with Edge Sampling.
The Price of Governance: A Middle Ground Solution to Coordination in Organizational Control.
On the Tree Representations of Dichotomous Preferences.
Complexity of Manipulating and Controlling Approval-Based Multiwinner Voting.
Large-Scale Home Energy Management Using Entropy-Based Collective Multiagent Deep Reinforcement Learning Framework.
Towards Efficient Detection and Optimal Response against Sophisticated Opponents.
On Strategyproof Conference Peer Review.
Exploring the Task Cooperation in Multi-goal Visual Navigation.
A Regularized Opponent Model with Maximum Entropy Objective.
Aggregating Incomplete Pairwise Preferences by Weight.
Model-Free Model Reconciliation.
Preferences Single-Peaked on a Tree: Sampling and Tree Recognition.
Sybil-Resilient Reality-Aware Social Choice.
Multi-Population Congestion Games With Incomplete Information.
Ridesharing with Driver Location Preferences.
Ad Hoc Teamwork With Behavior Switching Agents.
Approval-Based Elections and Distortion of Voting Rules.
Priority Inheritance with Backtracking for Iterative Multi-agent Path Finding.
Imitative Attacker Deception in Stackelberg Security Games.
A Probabilistic Logic for Resource-Bounded Multi-Agent Systems.
Learning Swarm Behaviors using Grammatical Evolution and Behavior Trees.
FaRM: Fair Reward Mechanism for Information Aggregation in Spontaneous Localized Settings.
Reachability Games in Dynamic Epistemic Logic.
Graphical One-Sided Markets.
Leadership in Congestion Games: Multiple User Classes and Non-Singleton Actions.
Multi-Robot Planning Under Uncertain Travel Times and Safety Constraints.
Computational Aspects of Equilibria in Discrete Preference Games.
Computing Approximate Equilibria in Sequential Adversarial Games by Exploitability Descent.
Value Function Transfer for Deep Multi-Agent Reinforcement Learning Based on N-Step Returns.
Integrating Decision Sharing with Prediction in Decentralized Planning for Multi-Agent Coordination under Uncertainty.
Improved Heuristics for Multi-Agent Path Finding with Conflict-Based Search.
Diffusion and Auction on Graphs.
Temporal Information Design in Contests.
Automated Negotiation with Gaussian Process-based Utility Models.
Correlating Preferences and Attributes: Nearly Single-Crossing Profiles.
A Quantitative Analysis of Multi-Winner Rules.
Almost Envy-Freeness in Group Resource Allocation.
Neural Networks for Predicting Human Interactions in Repeated Games.
Multigoal Committee Selection.
An Ordinal Banzhaf Index for Social Ranking.
The Interplay of Emotions and Norms in Multiagent Systems.
Robustness against Agent Failure in Hedonic Games.
Explicitly Coordinated Policy Iteration.
Compact Representation of Value Function in Partially Observable Stochastic Games.
Achieving a Fairer Future by Changing the Past.
Swarm Engineering Through Quantitative Measurement of Swarm Robotic Principles in a 10, 000 Robot Swarm.
On Computational Tractability for Rational Verification.
On Succinct Encodings for the Tournament Fixing Problem.
An Asymptotically Optimal VCG Redistribution Mechanism for the Public Project Problem.
Identifying vulnerabilities in trust and reputation systems.
On the Efficiency and Equilibria of Rich Ads.
Improving Nash Social Welfare Approximations.
Average-case Analysis of the Assignment Problem with Independent Preferences.
Equitable Allocations of Indivisible Goods.
Reallocating Multiple Facilities on the Line.
Schelling Games on Graphs.
Protecting Elections by Recounting Ballots.
Equilibrium Characterization for Data Acquisition Games.
Spotting Collective Behaviour of Online Frauds in Customer Reviews.
A Parameterized Perspective on Protecting Elections.
Preferred Deals in General Environments.
AsymDPOP: Complete Inference for Asymmetric Distributed Constraint Optimization Problems.
Anytime Heuristic for Weighted Matching Through Altruism-Inspired Behavior.
Civic Crowdfunding for Agents with Negative Valuations and Agents with Asymmetric Beliefs.
Exploiting Social Influence to Control Elections Based on Scoring Rules.
A Value-based Trust Assessment Model for Multi-agent Systems.
Cap-and-Trade Emissions Regulation: A Strategic Analysis.
Network Formation under Random Attack and Probabilistic Spread.
ATSIS: Achieving the Ad hoc Teamwork by Sub-task Inference and Selection.
Dispatching Through Pricing: Modeling Ride-Sharing and Designing Dynamic Prices.
Election with Bribe-Effect Uncertainty: A Dichotomy Result.
Approximately Maximizing the Broker's Profit in a Two-sided Market.
Reachability and Coverage Planning for Connected Agents.
Maximin-Aware Allocations of Indivisible Goods.
On the Problem of Assigning PhD Grants.
Be a Leader or Become a Follower: The Strategy to Commit to with Multiple Leaders.
A Contribution to the Critique of Liquid Democracy.
An Experimental View on Committees Providing Justified Representation.
Optimality and Nash Stability in Additive Separable Generalized Group Activity Selection Problems.
Fairness Towards Groups of Agents in the Allocation of Indivisible Items.
Strategy Logic with Simple Goals: Tractable Reasoning about Strategies.
The Price of Fairness for Indivisible Goods.
How Hard Is the Manipulative Design of Scoring Systems?.
Stable and Envy-free Partitions in Hedonic Games.
Strategyproof and Approximately Maxmin Fair Share Allocation of Chores.
Fair Allocation of Indivisible Goods and Chores.
Weighted Maxmin Fair Share Allocation of Indivisible Chores.
Multi-Agent Pathfinding with Continuous Time.
Probabilistic Strategy Logic.
Strategic Signaling for Selling Information Goods.
An Efficient Algorithm for Skeptical Preferred Acceptance in Dynamic Argumentation Frameworks.
Portioning Using Ordinal Preferences: Fairness and Efficiency.
Flexible Representative Democracy: An Introduction with Binary Issues.
