ijcai85

ijcai 2017 论文列表

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, IJCAI 2017, Melbourne, Australia, August 19-25, 2017.

Become Popular in SNS: Tag Recommendation using FolkPopularityRank to Enhance Social Popularity.
Emergency Evacuation Simulator (EES) - a Tool for Planning Community Evacuations in Australia.
Limbo: A Reasoning System for Limited Belief.
Real-Time UAV Maneuvering via Automated Planning in Simulations.
Speech-based Medical Decision Support in VR using a Deep Neural Network (Demonstration).
Automated Planning for Urban Traffic Management.
A Goal-Oriented Meaning-based Statistical Multi-Step Math Word Problem Solver with Understanding, Reasoning and Explanation.
Omniscient Debugging for GOAL Agents in Eclipse (Demonstration).
DISA: A Scientific Writing Advisor with Deep Information Structure Analysis.
Libratus: The Superhuman AI for No-Limit Poker.
Refinement of Intentions.
Towards A Relational Approach For Tool Creation By Robots.
Searching for Well-Behaved Fragments of Halpern-Shoham Logic.
Deep Abnormality Detection in Video Data.
Towards Trust, Transparency and Liability in AI / AS systems.
Search Strategies as Synchronous Processes (Extended Abstract).
The Role of Textualisation and Argumentation in Understanding the Machine Learning Process.
Using Multiagents for Context-Aware Adaptive Biometrics.
Fuzzy Logic Model for Digital Forensics: A Trade-off between Accuracy, Complexity and Interpretability.
Modeling Bias Reduction Strategies in a Biased Agent.
AToM: An Analogical Theory of Mind.
Teaching Robots through Situated Interactive Dialogue and Visual Demonstrations.
Operationalizing Operational Logics: Semiotic Knowledge Representations for Interactive Systems.
Nonparametric Online Machine Learning with Kernels.
Curriculum Learning in Reinforcement Learning.
Probabilistic Inference in Hybrid Domains.
Multi-Agent Systems of Inverse Reinforcement Learners in Complex Games.
Human-Like Agents for Repeated Negotiation.
Resilient Control and Safety for Multi-Agent Cyber-Physical Systems.
Machine Learning Techniques for MultiAgent Systems.
Stochastic Constraint Programming.
On the Complexity and Expressiveness of Automated Planning Languages Supporting Temporal Reasoning.
Efficient Algorithms And Representations For Chance-constrained Mixed Constraint Programming.
Constructive Recommendation.
SAT-Based Approaches for the General High School Timetabling Problem.
Online Algorithm Selection.
Understanding and Measuring Collective Intelligence Across Different Cognitive Systems: An Information-Theoretic Approach.
Learning Multi-faceted Knowledge Graph Embeddings for Natural Language Processing.
A Framework for Long-Term Learning Systems.
Securing and scaling cryptocurrencies.
Improving Group Decision-Making by Artificial Intelligence.
Unsupervised Learning via Total Correlation Explanation.
Reinforcement mechanism design.
Towards Certified Unsolvability in Classical Planning.
Multimodal News Article Analysis.
Knowledge Engineering for Intelligent Decision Support.
Learning from Data Heterogeneity: Algorithms and Applications.
Committee Scoring Rules: A Call to Arms.
Logic meets Probability: Towards Explainable AI Systems for Uncertain Worlds.
Game Theoretic Analysis of Security and Sustainability.
Robotic Strategic Behavior in Adversarial Environments.
POPPONENT: Highly accurate, individually and socially efficient opponent preference model in bilateral multi issue negotiations (Extended Abstract).
Text Rewriting Improves Semantic Role Labeling (Extended Abstract).
Local Search for Minimum Weight Dominating Set with Two-Level Configuration Checking and Frequency Based Scoring Function (Extended Abstract).
Exploiting Causality for Selective Belief Filtering in Dynamic Bayesian Networks (Extended Abstract).
Robots in Retirement Homes: Applying Off-the-Shelf Planning and Scheduling to a Team of Assistive Robots (Extended Abstract).
A generic approach to planning in the presence of incomplete information: Theory and implementation (Extended Abstract).
On the Expressivity of Inconsistency Measures (Extended Abstract).
Some Properties of Batch Value of Information in the Selection Problem (Extended Abstract).
Evaluating Epistemic Negation in Answer Set Programming (Extended Abstract).
Generating Models of a Matched Formula With a Polynomial Delay (Extended Abstract).
News Across Languages - Cross-Lingual Document Similarity and Event Tracking (Extended Abstract).
Construction of System of Spheres-based Transitively Relational Partial Meet Multiple Contractions: An Impossibility Result (Extended Abstract).
Relations Between Spatial Calculi About Directions and Orientations (Extended Abstract).
Approximate Value Iteration with Temporally Extended Actions (Extended Abstract).
CCEHC: An Efficient Local Search Algorithm for Weighted Partial Maximum Satisfiability (Extended Abstract).
AutoFolio: An Automatically Configured Algorithm Selector (Extended Abstract).
On Redundant Topological Constraints (Extended Abstract).
Automated Conjecturing I: Fajtlowicz's Dalmatian Heuristic Revisited (Extended Abstract).
New Canonical Representations by Augmenting OBDDs with Conjunctive Decomposition (Extended Abstract).
Computer Models Solving Intelligence Test Problems: Progress and Implications (Extended Abstract).
The Ceteris Paribus Structure of Logics of Game Forms (Extended Abstract).
Coherent Predictive Inference under Exchangeability with Imprecise Probabilities (Extended Abstract).
Bayesian Network Structure Learning with Integer Programming: Polytopes, Facets and Complexity (Extended Abstract).
Efficient Mechanism Design for Online Scheduling (Extended Abstract).
On Minimum Representations of Matched Formulas (Extended Abstract).
A New Semantics for Overriding in Description Logics (Extended Abstract).
Automatic Description Generation from Images: A Survey of Models, Datasets, and Evaluation Measures (Extended Abstract).
Robust Multilingual Named Entity Recognition with Shallow Semi-supervised Features (Extended Abstract).
Maximizing Awareness about HIV in Social Networks of Homeless Youth with Limited Information.
I-dual: Solving Constrained SSPs via Heuristic Search in the Dual Space.
Value Iteration Networks.
Local Topic Discovery via Boosted Ensemble of Nonnegative Matrix Factorization.
Evaluating Market User Interfaces for Electric Vehicle Charging using Bid2Charge.
Adapting Deep Network Features to Capture Psychological Representations: An Abridged Report.
Grounding Abstract Spatial Concepts for Language Interaction with Robots.
nanoCoP: Natural Non-clausal Theorem Proving.
KSP: A Resolution-based Prover for Multimodal K, Abridged Report.
Dynamical System-Based Motion Planning for Multi-Arm Systems: Reaching for Moving Objects.
The Many Benefits of Annotator Rationales for Relevance Judgments.
Competence Guided Model for Casebase Maintenance.
Self-Adjusting Memory: How to Deal with Diverse Drift Types.
A SAT Approach to Branchwidth.
On Thompson Sampling and Asymptotic Optimality.
Blockedness in Propositional Logic: Are You Satisfied With Your Neighborhood?
An End-to-End System for Accomplishing Tasks with Modular Robots: Perspectives for the AI community.
Learning and Applying Case Adaptation Rules for Classification: An Ensemble Approach.
Summary: Multi-Agent Path Finding with Kinematic Constraints.
Solving Very Hard Problems: Cube-and-Conquer, a Hybrid SAT Solving Method.
First-Order Modular Logic Programs and their Conservative Extensions (Extended Abstract).
Model Accuracy and Runtime Tradeoff in Distributed Deep Learning: A Systematic Study.
Multi-Type Activity Recognition from a Robot's Viewpoint.
Using Constraint Programming to solve a Cryptanalytic Problem.
Which is the Fairest (Rent Division) of Them All? [Extended Abstract].
Lexicons on Demand: Neural Word Embeddings for Large-Scale Text Analysis.
Lessons from the Amazon Picking Challenge: Four Aspects of Building Robotic Systems.
Enhancing Crowdworkers' Vigilance.
User-Based Opinion-based Recommendation.
Intuitionistic Layered Graph Logic.
Ensuring Rapid Mixing and Low Bias for Asynchronous Gibbs Sampling.
Predicting Human Similarity Judgments with Distributional Models: The Value of Word Associations.
Efficient Techniques for Crowdsourced Top-k Lists.
Open-World Probabilistic Databases: An Abridged Report.
Concerning Referring Expressions in Query Answers.
A Verified SAT Solver Framework with Learn, Forget, Restart, and Incrementality.
Unsatisfiable Core Shrinking for Anytime Answer Set Optimization.
Rationalisation of Profiles of Abstract Argumentation Frameworks: Extended Abstract.
Online Decision-Making for Scalable Autonomous Systems.
Privacy and Autonomous Systems.
Should Robots be Obedient?
Concrete Problems for Autonomous Vehicle Safety: Advantages of Bayesian Deep Learning.
Context-Based Reasoning on Privacy in Internet of Things.
Achieving Coordination in Multi-Agent Systems by Stable Local Conventions under Community Networks.
On Automating the Doctrine of Double Effect.
A Goal Reasoning Agent for Controlling UAVs in Beyond-Visual-Range Air Combat.
Reinforcement Learning with a Corrupted Reward Channel.
Responsible Autonomy.
Algorithmic Bias in Autonomous Systems.
When Will Negotiation Agents Be Able to Represent Us? The Challenges and Opportunities for Autonomous Negotiators.
Plato's Cave in the Dempster-Shafer land-the Link between Pignistic and Plausibility Transformations.
Approximating Discrete Probability Distribution of Image Emotions by Multi-Modal Features Fusion.
Dynamic Programming Bipartite Belief Propagation For Hyper Graph Matching.
Single-Image 3D Scene Parsing Using Geometric Commonsense.
Robust Quadratic Programming for Price Optimization.
XOR-Sampling for Network Design with Correlated Stochastic Events.
Scalable Estimation of Dirichlet Process Mixture Models on Distributed Data.
Order Statistics for Probabilistic Graphical Models.
Efficient Inference for Untied MLNs.
Weighted Model Integration with Orthogonal Transformations.
Variational Mixtures of Gaussian Processes for Classification.
Coarse-to-Fine Lifted MAP Inference in Computer Vision.
Incremental Decision Making Under Risk with the Weighted Expected Utility Model.
Fair and Efficient Social Choice in Dynamic Settings.
COG-DICE: An Algorithm for Solving Continuous-Observation Dec-POMDPs.
Adaptive Elicitation of Preferences under Uncertainty in Sequential Decision Making Problems.
Image Gradient-based Joint Direct Visual Odometry for Stereo Camera.
Is My Object in This Video? Reconstruction-based Object Search in Videos.
Cross-Granularity Graph Inference for Semantic Video Object Segmentation.
Learning to Hallucinate Face Images via Component Generation and Enhancement.
Fast Preprocessing for Robust Face Sketch Synthesis.
Combining Models from Multiple Sources for RGB-D Scene Recognition.
Maintaining Communication in Multi-Robot Tree Coverage.
Temporal Grounding Graphs for Language Understanding with Accrued Visual-Linguistic Context.
Salient Object Detection with Semantic Priors.
Locality Preserving Matching.
Dual Track Multimodal Automatic Learning through Human-Robot Interaction.
Bridging the Gap between Observation and Decision Making: Goal Recognition and Flexible Resource Allocation in Dynamic Network Interdiction.
A Scalable Approach to Chasing Multiple Moving Targets with Multiple Agents.
Hierarchical Task Network Planning with Task Insertion and State Constraints.
New Metrics and Algorithms for Stochastic Goal Recognition Design Problems.
Heuristic Online Goal Recognition in Continuous Domains.
Temporal Planning for Compilation of Quantum Approximate Optimization Circuits.
Mechanism Design for Strategic Project Scheduling.
From Qualitative to Quantitative Dominance Pruning for Optimal Planning.
Robust Advertisement Allocation.
An Improved Approximation Algorithm for the Subpath Planning Problem and Its Generalization.
Efficient, Safe, and Probably Approximately Complete Learning of Action Models.
Search and Learn: On Dead-End Detectors, the Traps they Set, and Trap Learning.
Generating Context-Free Grammars using Classical Planning.
Landmarks for Numeric Planning Problems.
Lossy Compression of Pattern Databases Using Acyclic Random Hypergraphs.
Deceptive Path-Planning.
Integrating Answer Set Programming with Semantic Dictionaries for Robot Task Planning.
Equi-Reward Utility Maximizing Design in Stochastic Environments.
Factorized Asymptotic Bayesian Policy Search for POMDPs.
Numeric Planning via Abstraction and Policy Guided Search.
Switched Linear Multi-Robot Navigation Using Hierarchical Model Predictive Control.
Softpressure: A Schedule-Driven Backpressure Algorithm for Coping with Network Congestion.
Intelligent Belief State Sampling for Conformant Planning.
Beyond Forks: Finding and Ranking Star Factorings for Decoupled Search.
On Creating Complementary Pattern Databases.
Purely Declarative Action Descriptions are Overrated: Classical Planning with Simulators.
Additive Merge-and-Shrink Heuristics for Diverse Action Costs.
Faster Conflict Generation for Dynamic Controllability.
Reduction Techniques for Model Checking and Learning in MDPs.
Efficient Optimal Search under Expensive Edge Cost Computation.
Iterative Entity Alignment via Joint Knowledge Embeddings.
Maximum Expected Likelihood Estimation for Zero-resource Neural Machine Translation.
Entity Suggestion with Conceptual Expanation.
Automatic Generation of Grounded Visual Questions.
Segmenting Chinese Microtext: Joint Informal-Word Detection and Segmentation with Neural Networks.
AGRA: An Analysis-Generation-Ranking Framework for Automatic Abbreviation from Paper Titles.
Learning Conversational Systems that Interleave Task and Non-Task Content.
A Correlated Topic Model Using Word Embeddings.
Lexical Sememe Prediction via Word Embeddings and Matrix Factorization.
Fast Parallel Training of Neural Language Models.
Symbolic Priors for RNN-based Semantic Parsing.
Improved Neural Machine Translation with Source Syntax.
Learning to Identify Ambiguous and Misleading News Headlines.
A Variational Autoencoding Approach for Inducing Cross-lingual Word Embeddings.
A Neural Model for Joint Event Detection and Summarization.
DDoS Event Forecasting using Twitter Data.
Bilateral Multi-Perspective Matching for Natural Language Sentences.
Learning Sentence Representation with Guidance of Human Attention.
Joint Learning on Relevant User Attributes in Micro-blog.
Conditional Generative Adversarial Networks for Commonsense Machine Comprehension.
Multi-Modal Word Synset Induction.
From Neural Sentence Summarization to Headline Generation: A Coarse-to-Fine Approach.
Finding Prototypes of Answers for Improving Answer Sentence Selection.
Automatic Assessment of Absolute Sentence Complexity.
Parsing Natural Language Conversations using Contextual Cues.
Why Can't You Convince Me? Modeling Weaknesses in Unpersuasive Arguments.
Inverted Bilingual Topic Models for Lexicon Extraction from Non-parallel Data.
Interactive Attention Networks for Aspect-Level Sentiment Classification.
Adaptive Semantic Compositionality for Sentence Modelling.
Dynamic Compositional Neural Networks over Tree Structure.
A Structural Representation Learning for Multi-relational Networks.
How Unlabeled Web Videos Help Complex Event Detection?
MAT: A Multimodal Attentive Translator for Image Captioning.
SWIM: A Simple Word Interaction Model for Implicit Discourse Relation Recognition.
Learning to Explain Entity Relationships by Pairwise Ranking with Convolutional Neural Networks.
Understanding and Exploiting Language Diversity.
Effective Deep Memory Networks for Distant Supervised Relation Extraction.
An Attention-based Regression Model for Grounding Textual Phrases in Images.
Stance Classification with Target-specific Neural Attention.
Solving Probability Problems in Natural Language.
Joint Training for Pivot-based Neural Machine Translation.
Multimodal Storytelling via Generative Adversarial Imitation Learning.
A Feature-Enriched Neural Model for Joint Chinese Word Segmentation and Part-of-Speech Tagging.
A Group-Based Personalized Model for Image Privacy Classification and Labeling.
Efficient Label Contamination Attacks Against Black-Box Learning Models.
Optimal Escape Interdiction on Transportation Networks.
A Causal Framework for Discovering and Removing Direct and Indirect Discrimination.
Efficient Private ERM for Smooth Objectives.
Socialized Word Embeddings.
No Time to Observe: Adaptive Influence Maximization with Partial Feedback.
A Convolutional Approach for Misinformation Identification.
Fast Network Embedding Enhancement via High Order Proximity Approximation.
Beyond Universal Saliency: Personalized Saliency Prediction with Multi-task CNN.
Predicting Alzheimer's Disease Cognitive Assessment via Robust Low-Rank Structured Sparse Model.
Online Reputation Fraud Campaign Detection in User Ratings.
A Trust-based Mixture of Gaussian Processes Model for Reliable Regression in Participatory Sensing.
Predicting the Quality of Short Narratives from Social Media.
Interactive Narrative Personalization with Deep Reinforcement Learning.
The Minds of Many: Opponent Modeling in a Stochastic Game.
Depression Detection via Harvesting Social Media: A Multimodal Dictionary Learning Solution.
A Monte Carlo Tree Search approach to Active Malware Analysis.
Leveraging Human Knowledge in Tabular Reinforcement Learning: A Study of Human Subjects.
When Security Games Hit Traffic: Optimal Traffic Enforcement Under One Sided Uncertainty.
Cognitive-Inspired Conversational-Strategy Reasoner for Socially-Aware Agents.
Unified Representation and Lifted Sampling for Generative Models of Social Networks.
Quantifying Aspect Bias in Ordinal Ratings using a Bayesian Approach.
Thwarting Vote Buying Through Decoy Ballots.
Blue Skies: A Methodology for Data-Driven Clear Sky Modelling.
Staying Ahead of the Game: Adaptive Robust Optimization for Dynamic Allocation of Threat Screening Resources.
Adversarial Generation of Real-time Feedback with Neural Networks for Simulation-based Training.
Tactics of Adversarial Attack on Deep Reinforcement Learning Agents.
How to Keep a Knowledge Base Synchronized with Its Encyclopedia Source.
Defending Against Man-In-The-Middle Attack in Repeated Games.
Stratified Strategy Selection for Unit Control in Real-Time Strategy Games.
Exploring Personalized Neural Conversational Models.
Fashion Style Generator.
Who to Invite Next? Predicting Invitees of Social Groups.
Game Engine Learning from Video.
Modeling Physicians' Utterances to Explore Diagnostic Decision-making.
Comparing Strategic Secrecy and Stackelberg Commitment in Security Games.
Playing Repeated Network Interdiction Games with Semi-Bandit Feedback.
DeepAM: Migrate APIs with Multi-modal Sequence to Sequence Learning.
Focused Depth-first Proof Number Search using Convolutional Neural Networks for the Game of Hex.
Social Pressure in Opinion Games.
Exploiting Music Play Sequence for Music Recommendation.
Opinion-aware Knowledge Graph for Political Ideology Detection.
Deep Multi-species Embedding.
Networked Fairness in Cake Cutting.
Cake Cutting: Envy and Truth.
Understanding People Lifestyles: Construction of Urban Movement Knowledge Graph from GPS Trajectory.
Object Recognition with and without Objects.
What to Do Next: Modeling User Behaviors by Time-LSTM.
Dependency Exploitation: A Unified CNN-RNN Approach for Visual Emotion Recognition.
No Learner Left Behind: On the Complexity of Teaching Multiple Learners Simultaneously.
Adaptive Hypergraph Learning for Unsupervised Feature Selection.
Deep Graphical Feature Learning for Face Sketch Synthesis.
Locality Constrained Deep Supervised Hashing for Image Retrieval.
Diverse Neuron Type Selection for Convolutional Neural Networks.
Deep Forest: Towards An Alternative to Deep Neural Networks.
Binary Linear Compression for Multi-label Classification.
Tensor Completion with Side Information: A Riemannian Manifold Approach.
Microblog Sentiment Classification via Recurrent Random Walk Network Learning.
Link Prediction via Ranking Metric Dual-Level Attention Network Learning.
Video Question Answering via Hierarchical Spatio-Temporal Attention Networks.
TUCH: Turning Cross-view Hashing into Single-view Hashing via Generative Adversarial Nets.
Deep Multiple Instance Hashing for Object-based Image Retrieval.
ContextCare: Incorporating Contextual Information Networks to Representation Learning on Medical Forum Data.
Deep Optical Flow Estimation Via Multi-Scale Correspondence Structure Learning.
Hierarchical Feature Selection with Recursive Regularization.
Random Shifting for CNN: a Solution to Reduce Information Loss in Down-Sampling Layers.
Learning Discriminative Recommendation Systems with Side Information.
Tensor Based Knowledge Transfer Across Skill Categories for Robot Control.
Weighted Double Q-learning.
Multimodal Linear Discriminant Analysis via Structural Sparsity.
Multi-Instance Learning with Key Instance Shift.
Robust Regression via Heuristic Hard Thresholding.
Global-residual and Local-boundary Refinement Networks for Rectifying Scene Parsing Predictions.
Hashtag Recommendation for Multimodal Microblog Using Co-Attention Network.
DRLnet: Deep Difference Representation Learning Network and An Unsupervised Optimization Framework.
Adaptively Unified Semi-supervised Learning for Cross-Modal Retrieval.
Adaptive Manifold Regularized Matrix Factorization for Data Clustering.
ME-MD: An Effective Framework for Neural Machine Translation with Multiple Encoders and Decoders.
A Generalized Recurrent Neural Architecture for Text Classification with Multi-Task Learning.
User Profile Preserving Social Network Embedding.
Deep-dense Conditional Random Fields for Object Co-segmentation.
Fast Stochastic Variance Reduced ADMM for Stochastic Composition Optimization.
Open Category Classification by Adversarial Sample Generation.
Single-Pass PCA of Large High-Dimensional Data.
Link Prediction with Spatial and Temporal Consistency in Dynamic Networks.
Privileged Multi-label Learning.
Learning Co-Substructures by Kernel Dependence Maximization.
A Deep Neural Network for Chinese Zero Pronoun Resolution.
Learning Mahalanobis Distance Metric: Considering Instance Disturbance Helps.
Efficient Inexact Proximal Gradient Algorithm for Nonconvex Problems.
Multi-Task Deep Reinforcement Learning for Continuous Action Control.
A Robust Noise Resistant Algorithm for POI Identification from Flickr Data.
Modal Consistency based Pre-Trained Multi-Model Reuse.
Learning to Read Irregular Text with Attention Mechanisms.
Positive unlabeled learning via wrapper-based adaptive sampling.
Joint Image Emotion Classification and Distribution Learning via Deep Convolutional Neural Network.
Life-Stage Modeling by Customer-Manifold Embedding.
Learning Discriminative Correlation Subspace for Heterogeneous Domain Adaptation.
Predicting Human Interaction via Relative Attention Model.
Semi-Supervised Deep Hashing with a Bipartite Graph.
FolkPopularityRank: Tag Recommendation for Enhancing Social Popularity using Text Tags in Content Sharing Services.
When Does Label Propagation Fail? A View from a Network Generative Model.
Tensor Decomposition with Missing Indices.
Multiple Indefinite Kernel Learning for Feature Selection.
Deep Matrix Factorization Models for Recommender Systems.
Tag-Aware Personalized Recommendation Using a Hybrid Deep Model.
Stochastic Online Anomaly Analysis for Streaming Time Series.
Multi-Positive and Unlabeled Learning.
Incomplete Label Distribution Learning.
Feature Selection via Scaling Factor Integrated Multi-Class Support Vector Machines.
Multi-view Feature Learning with Discriminative Regularization.
Multi-Class Support Vector Machine via Maximizing Multi-Class Margins.
Linear Manifold Regularization with Adaptive Graph for Semi-supervised Dimensionality Reduction.
Image-embodied Knowledge Representation Learning.
Dynamic Multi-View Hashing for Online Image Retrieval.
SVD-free Convex-Concave Approaches for Nuclear Norm Regularization.
Attentional Factorization Machines: Learning the Weight of Feature Interactions via Attention Networks.
Dual Inference for Machine Learning.
Query-Driven Discovery of Anomalous Subgraphs in Attributed Graphs.
Sequence Prediction with Unlabeled Data by Reward Function Learning.
Deep Context: A Neural Language Model for Large-scale Networked Documents.
Modeling Trajectories with Recurrent Neural Networks.
Unsupervised Deep Video Hashing with Balanced Rotation.
Discriminant Tensor Dictionary Learning with Neighbor Uncorrelation for Image Set Based Classification.
Sequential Prediction of Social Media Popularity with Deep Temporal Context Networks.
Learning from Demonstrations with High-Level Side Information.
Deep Descriptor Transforming for Image Co-Localization.
Group-wise Deep Co-saliency Detection.
Supervised Deep Features for Software Functional Clone Detection by Exploiting Lexical and Syntactical Information in Source Code.
Improving Reinforcement Learning with Confidence-Based Demonstrations.
Doubly Sparsifying Network.
On Gleaning Knowledge from Multiple Domains for Active Learning.
Approximate Large-scale Multiple Kernel k-means Using Deep Neural Network.
Multiple Kernel Clustering Framework with Improved Kernels.
Fast Change Point Detection on Dynamic Social Networks.
Cascade Dynamics Modeling with Attention-based Recurrent Neural Network.
App Download Forecasting: An Evolutionary Hierarchical Competition Approach.
Multiple Medoids based Multi-view Relational Fuzzy Clustering with Minimax Optimization.
Obtaining High-Quality Label by Distinguishing between Easy and Hard Items in Crowdsourcing.
Interactive Image Segmentation via Pairwise Likelihood Learning.
A Sequence Labeling Convolutional Network and Its Application to Handwritten String Recognition.
Instance-Level Label Propagation with Multi-Instance Learning.
Angle Principal Component Analysis.
Convolutional 2D LDA for Nonlinear Dimensionality Reduction.
Multi-Component Nonnegative Matrix Factorization.
Combining Knowledge with Deep Convolutional Neural Networks for Short Text Classification.
Active Learning for Black-Box Semantic Role Labeling with Neural Factors.
Tag Disentangled Generative Adversarial Network for Object Image Re-rendering.
Locality Preserving Projections for Grassmann manifold.
Sifting Common Information from Many Variables.
Scaling Active Search using Linear Similarity Functions.
COBRA: A Fast and Simple Method for Active Clustering with Pairwise Constraints.
TransNet: Translation-Based Network Representation Learning for Social Relation Extraction.
Disambiguating Energy Disaggregation: A Collective Probabilistic Approach.
Retaining Data from Streams of Social Platforms with Minimal Regret.
From Ensemble Clustering to Multi-View Clustering.
Inverse Covariance Estimation with Structured Groups.
Robust Survey Aggregation with Student-t Distribution and Sparse Representation.
Student-t Process Regression with Student-t Likelihood.
Bayesian Dynamic Mode Decomposition.
MRLR: Multi-level Representation Learning for Personalized Ranking in Recommendation.
CHARDA: Causal Hybrid Automata Recovery via Dynamic Analysis.
Correlational Dueling Bandits with Application to Clinical Treatment in Large Decision Spaces.
Deep Supervised Hashing with Nonlinear Projections.
Vertex-Weighted Hypergraph Learning for Multi-View Object Classification.
Forecast the Plausible Paths in Crowd Scenes.
End-to-end optimization of goal-driven and visually grounded dialogue systems.
Fast Sparse Gaussian Markov Random Fields Learning Based on Cholesky Factorization.
Two dimensional Large Margin Nearest Neighbor for Matrix Classification.
Recommendation vs Sentiment Analysis: A Text-Driven Latent Factor Model for Rating Prediction with Cold-Start Awareness.
Hierarchical LSTM with Adjusted Temporal Attention for Video Captioning.
Learning Hedonic Games.
Learning with Previously Unseen Features.
Accelerated Doubly Stochastic Gradient Algorithm for Large-scale Empirical Risk Minimization.
Learning Multi-level Region Consistency with Dense Multi-label Networks for Semantic Segmentation.
Compressed Nonparametric Language Modelling.
Locally Consistent Bayesian Network Scores for Multi-Relational Data.
Convolutional-Match Networks for Question Answering.
LMPP: A Large Margin Point Process Combining Reinforcement and Competition for Modeling Hashtag Popularity.
See without looking: joint visualization of sensitive multi-site datasets.
Right for the Right Reasons: Training Differentiable Models by Constraining their Explanations.
Distributed Accelerated Proximal Coordinate Gradient Methods.
Sense Beauty by Label Distribution Learning.
Robust Softmax Regression for Multi-class Classification with Self-Paced Learning.
Stacking With Auxiliary Features.
A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction.
Improving Stochastic Block Models by Incorporating Power-Law Degree Characteristic.
On Subset Selection with General Cost Constraints.
Optimizing Ratio of Monotone Set Functions.
Boosted Zero-Shot Learning with Semantic Correlation Regularization.
Flexible Orthogonal Neighborhood Preserving Embedding.
Learning Homophily Couplings from Non-IID Data for Joint Feature Selection and Noise-Resilient Outlier Detection.
Discovering Relevance-Dependent Bicluster Structure from Relational Data.
SEVEN: Deep Semi-supervised Verification Networks.
Self-weighted Multiview Clustering with Multiple Graphs.
Joint Capped Norms Minimization for Robust Matrix Recovery.
Discriminative Bayesian Nonparametric Clustering.
Large-scale Online Kernel Learning with Random Feature Reparameterization.
Autonomous Task Sequencing for Customized Curriculum Design in Reinforcement Learning.
Learning Feature Engineering for Classification.
Self-Paced Multitask Learning with Shared Knowledge.
Thresholding Bandits with Augmented UCB.
Completely Heterogeneous Transfer Learning with Attention - What And What Not To Transfer.
Rescale-Invariant SVM for Binary Classification.
Beyond the Nystrom Approximation: Speeding up Spectral Clustering using Uniform Sampling and Weighted Kernel k-means.
Logistic Markov Decision Processes.
Exemplar-centered Supervised Shallow Parametric Data Embedding.
Count-Based Exploration in Feature Space for Reinforcement Learning.
Cross-Domain Recommendation: An Embedding and Mapping Approach.
WALKING WALKing walking: Action Recognition from Action Echoes.
General Heterogeneous Transfer Distance Metric Learning via Knowledge Fragments Transfer.
Exploiting High-Order Information in Heterogeneous Multi-Task Feature Learning.
Symmetric Non-negative Latent Factor Models for Undirected Large Networks.
EigenNet: Towards Fast and Structural Learning of Deep Neural Networks.
Adaptive Semi-Supervised Learning with Discriminative Least Squares Regression.
Tracking the Evolution of Customer Purchase Behavior Segmentation via a Fragmentation-Coagulation Process.
Image Matching via Loopy RNN.
Sampling for Approximate Maximum Search in Factorized Tensor.
Dynamic Weighted Majority for Incremental Learning of Imbalanced Data Streams with Concept Drift.
JM-Net and Cluster-SVM for Aerial Scene Classification.
Learning User Dependencies for Recommendation.
Deep Ordinal Regression Based on Data Relationship for Small Datasets.
Understanding How Feature Structure Transfers in Transfer Learning.
Adaptive Group Sparse Multi-task Learning via Trace Lasso.
Learning Concise Representations of Users' Influences through Online Behaviors.
Cause-Effect Knowledge Acquisition and Neural Association Model for Solving A Set of Winograd Schema Problems.
Accelerated Local Anomaly Detection via Resolving Attributed Networks.
Improving Learning-from-Crowds through Expert Validation.
Fast SVM Trained by Divide-and-Conquer Anchors.
Modeling Hebb Learning Rule for Unsupervised Learning.
Semi-supervised Orthogonal Graph Embedding with Recursive Projections.
DeepFacade: A Deep Learning Approach to Facade Parsing.
Locally Linear Factorization Machines.
Deep Neural Networks for High Dimension, Low Sample Size Data.
Regional Concept Drift Detection and Density Synchronized Drift Adaptation.
Hybrid Neural Networks for Learning the Trend in Time Series.
Discriminative Deep Hashing for Scalable Face Image Retrieval.
LoCaTe: Influence Quantification for Location Promotion in Location-based Social Networks.
Incomplete Attribute Learning with auxiliary labels.
Integrating Specialized Classifiers Based on Continuous Time Markov Chain.
End-to-End Adversarial Memory Network for Cross-domain Sentiment Classification.
Demystifying Neural Style Transfer.
CFNN: Correlation Filter Neural Network for Visual Object Tracking.
Classification and Representation Joint Learning via Deep Networks.
MAM-RNN: Multi-level Attention Model Based RNN for Video Captioning.
Locality Adaptive Discriminant Analysis.
Person Re-Identification by Deep Joint Learning of Multi-Loss Classification.
Self-paced Compensatory Deep Boltzmann Machine for Semi-Structured Document Embedding.
Online Robust Low-Rank Tensor Learning.
Affinity Learning for Mixed Data Clustering.
Multi-Stream Deep Similarity Learning Networks for Visual Tracking.
Reconstruction-based Unsupervised Feature Selection: An Embedded Approach.
Radar: Residual Analysis for Anomaly Detection in Attributed Networks.
Projective Low-rank Subspace Clustering via Learning Deep Encoder.
Large-scale Subspace Clustering by Fast Regression Coding.
Improving the Generalization Performance of Multi-class SVM via Angular Regularization.
Efficient Kernel Selection via Spectral Analysis.
Learning User's Intrinsic and Extrinsic Interests for Point-of-Interest Recommendation: A Unified Approach.
Self-paced Convolutional Neural Networks.
Effective Representing of Information Network by Variational Autoencoder.
High Dimensional Bayesian Optimization using Dropout.
Constrained Bayesian Reinforcement Learning via Approximate Linear Programming.
Name Nationality Classification with Recurrent Neural Networks.
Semantic Visualization for Short Texts with Word Embeddings.
Learning Sparse Representations in Reinforcement Learning with Sparse Coding.
Basket-Sensitive Personalized Item Recommendation.
Saliency Guided End-to-End Learning for Weakly Supervised Object Detection.
Earth Mover's Distance Pooling over Siamese LSTMs for Automatic Short Answer Grading.
Learning Latest Classifiers without Additional Labeled Data.
Decreasing Uncertainty in Planning with State Prediction.
Efficiency Through Procrastination: Approximately Optimal Algorithm Configuration with Runtime Guarantees.
DeepStory: Video Story QA by Deep Embedded Memory Networks.
Learning deep structured network for weakly supervised change detection.
Bernoulli Rank-1 Bandits for Click Feedback.
Modelling the Working Week for Multi-Step Forecasting using Gaussian Process Regression.
A Functional Dynamic Boltzmann Machine.
Confusion Graph: Detecting Confusion Communities in Large Scale Image Classification.
Improving Classification Accuracy of Feedforward Neural Networks for Spiking Neuromorphic Chips.
Variational Deep Embedding: An Unsupervised and Generative Approach to Clustering.
Theoretic Analysis and Extremely Easy Algorithms for Domain Adaptive Feature Learning.
Exploration of Tree-based Hierarchical Softmax for Recurrent Language Models.
Semi-supervised Learning over Heterogeneous Information Networks by Ensemble of Meta-graph Guided Random Walks.
Embedding-based Representation of Categorical Data by Hierarchical Value Coupling Learning.
Privacy Issues Regarding the Application of DNNs to Activity-Recognition using Wearables and Its Countermeasures by Use of Adversarial Training.
Adaptive Learning Rate via Covariance Matrix Based Preconditioning for Deep Neural Networks.
Ordinal Zero-Shot Learning.
Enhancing the Unified Features to Locate Buggy Files by Exploiting the Sequential Nature of Source Code.
Incremental Matrix Factorization: A Linear Feature Transformation Perspective.
Cross-modal Common Representation Learning by Hybrid Transfer Network.
Multi-instance multi-label active learning.
Cost-Effective Active Learning from Diverse Labelers.
Mention Recommendation for Twitter with End-to-end Memory Network.
Semi-supervised Max-margin Topic Model with Manifold Posterior Regularization.
Diversifying Personalized Recommendation with User-session Context.
Fast Recursive Low-rank Tensor Learning for Regression.
Storage Fit Learning with Unlabeled Data.
Category-aware Next Point-of-Interest Recommendation via Listwise Bayesian Personalized Ranking.
Nonlinear Maximum Margin Multi-View Learning with Adaptive Kernel.
Online Multitask Relative Similarity Learning.
Self-paced Mixture of Regressions.
Orthogonal and Nonnegative Graph Reconstruction for Large Scale Clustering.
Knowledge Transfer for Out-of-Knowledge-Base Entities : A Graph Neural Network Approach.
Instability Prediction in Power Systems using Recurrent Neural Networks.
Improved Strong Worst-case Upper Bounds for MDP Planning.
Understanding Users' Budgets for Recommendation with Hierarchical Poisson Factorization.
Synthesizing Samples for Zero-shot Learning.
SitNet: Discrete Similarity Transfer Network for Zero-shot Hashing.
Robust Asymmetric Bayesian Adaptive Matrix Factorization.
Improved Deep Embedded Clustering with Local Structure Preservation.
ROUTE: Robust Outlier Estimation for Low Rank Matrix Recovery.
Exclusivity Regularized Machine: A New Ensemble SVM Classifier.
A Density-based Nonparametric Model for Online Event Discovery from the Social Media Data.
DeepFM: A Factorization-Machine based Neural Network for CTR Prediction.
Extracting Visual Knowledge from the Web with Multimodal Learning.
Sample Efficient Policy Search for Optimal Stopping Domains.
Towards Understanding the Invertibility of Convolutional Neural Networks.
Neurogenesis-Inspired Dictionary Learning: Online Model Adaption in a Changing World.
Identifying Human Mobility via Trajectory Embeddings.
SVD-Based Screening for the Graphical Lasso.
On the Complexity of Learning from Label Proportions.
Dynamic Multi-Task Learning with Convolutional Neural Network.
Object Detection Meets Knowledge Graphs.
Improved Bounded Matrix Completion for Large-Scale Recommender Systems.
Top-k Supervise Feature Selection via ADMM for Integer Programming.
Learning to Learn Programs from Examples: Going Beyond Program Structure.
Clustering-Based Relational Unsupervised Representation Learning with an Explicit Distributed Representation.
Semi-Supervised Learning for Surface EMG-based Gesture Recognition.
Collaborative Rating Allocation.
Privileged Matrix Factorization for Collaborative Filtering.
Autoencoder Regularized Network For Driving Style Representation Learning.
Logic Tensor Networks for Semantic Image Interpretation.
Disguise Adversarial Networks for Click-through Rate Prediction.
Real-Time Navigation in Classical Platform Games via Skill Reuse.
Analogy-preserving functions: A way to extend Boolean samples.
Further Results on Predicting Cognitive Abilities for Adaptive Visualizations.
Stacked Similarity-Aware Autoencoders.
Optimal Feature Selection for Decision Robustness in Bayesian Networks.
End-to-End Prediction of Buffer Overruns from Raw Source Code via Neural Memory Networks.
Projection Free Rank-Drop Steps.
Training Group Orthogonal Neural Networks with Privileged Information.
Semi-supervised Feature Selection via Rescaled Linear Regression.
Scalable Normalized Cut with Improved Spectral Rotation.
Multilingual Knowledge Graph Embeddings for Cross-lingual Knowledge Alignment.
Importance-Aware Semantic Segmentation for Autonomous Driving System.
Data-driven Random Fourier Features using Stein Effect.
Encoding and Recall of Spatio-Temporal Episodic Memory in Real Time.
Multiple-Weight Recurrent Neural Networks.
SPMC: Socially-Aware Personalized Markov Chains for Sparse Sequential Recommendation.
Context Attentive Bandits: Contextual Bandit with Restricted Context.
Human-Centric Justification of Machine Learning Predictions.
Using Graphs of Classifiers to Impose Declarative Constraints on Semi-supervised Learning.
Unsupervised Learning of Deep Feature Representation for Clustering Egocentric Actions.
AccGenSVM: Selectively Transferring from Previous Hypotheses.
Handling Noise in Boolean Matrix Factorization.
Mining Convex Polygon Patterns with Formal Concept Analysis.
Efficient Reinforcement Learning with Hierarchies of Machines by Leveraging Internal Transitions.
Bayesian Aggregation of Categorical Distributions with Applications in Crowdsourcing.
Universal Reinforcement Learning Algorithms: Survey and Experiments.
Grounding of Human Environments and Activities for Autonomous Robots.
RHash: Robust Hashing via L_infinity-norm Distortion.
Contextual Covariance Matrix Adaptation Evolutionary Strategies.
A Unifying Framework for Probabilistic Belief Revision.
Symbolic LTLf Synthesis.
Role Forgetting for ALCOQH(universal role)-Ontologies Using an Ackermann-Based Approach.
Causal Discovery from Nonstationary/Heterogeneous Data: Skeleton Estimation and Orientation Determination.
Transfer Learning in Multi-Armed Bandits: A Causal Approach.
Proposing a Highly Accurate Hybrid Component-Based Factorised Preference Model in Recommender Systems.
Aggregating Crowd Wisdoms with Label-aware Autoencoders.
Knowledge Graph Representation with Jointly Structural and Textual Encoding.
Efficient Inference and Computation of Optimal Alternatives for Preference Languages Based On Lexicographic Models.
A Characterization Theorem for a Modal Description Logic.
Inferring Human Attention by Learning Latent Intentions.
Explicit Knowledge-based Reasoning for Visual Question Answering.
How a General-Purpose Commonsense Ontology can Improve Performance of Learning-Based Image Retrieval.
GDL-III: A Description Language for Epistemic General Game Playing.
On Computing World Views of Epistemic Logic Programs.
Efficiently Enforcing Path Consistency on Qualitative Constraint Networks by Use of Abstraction.
Fair Allocation based on Diminishing Differences.
A Reasoning System for a First-Order Logic of Limited Belief.
Conflict-driven ASP Solving with External Sources and Program Splits.
Efficient and Complete FD-solving for extended array constraints.
The Bag Semantics of Ontology-Based Data Access.
Generalized Target Assignment and Path Finding Using Answer Set Programming.
Dominance and Optimisation Based on Scale-Invariant Maximum Margin Preference Learning.
Contract Design for Energy Demand Response.
Context-aware Path Ranking for Knowledge Base Completion.
Logic on MARS: Ontologies for Generalised Property Graphs.
Ontology-Mediated Querying with the Description Logic EL: Trichotomy and Linear Datalog Rewritability.
A Data-Driven Approach to Infer Knowledge Base Representation for Natural Language Relations.
Temporalising Separation Logic for Planning with Search Control Knowledge.
Mapping Repair in Ontology-based Data Access Evolving Systems.
Induction of Interpretable Possibilistic Logic Theories from Relational Data.
On the Complexity of Enumerating the Extensions of Abstract Argumentation Frameworks.
Model Checking Multi-Agent Systems against LDLK Specifications.
Strong Syntax Splitting for Iterated Belief Revision.
Foundations of Declarative Data Analysis Using Limit Datalog Programs.
Query Conservative Extensions in Horn Description Logics with Inverse Roles.
Belief Manipulation Through Propositional Announcements.
ATL Strategic Reasoning Meets Correlated Equilibrium.
A General Multi-agent Epistemic Planner Based on Higher-order Belief Change.
Revisiting Unrestricted Rebut and Preferences in Structured Argumentation.
Characterising the Manipulability of Boolean Games.
Combining DL-Lite_{bool}^N with Branching Time: A gentle Marriage.
Nash Equilibria in Concurrent Games with Lexicographic Preferences.
Relatedness-based Multi-Entity Summarization.
Non-Determinism and the Dynamics of Knowledge.
The Tractability of the Shapley Value over Bounded Treewidth Matching Games.
What Can You Do with a Rock? Affordance Extraction via Word Embeddings.
Strategically knowing how.
Process Plan Controllers for Non-Deterministic Manufacturing Systems.
Lazy-Grounding for Answer Set Programs with External Source Access.
Bounded Timed Propositional Temporal Logic with Past Captures Timeline-based Planning with Bounded Constraints.
Streaming Multi-Context Systems.
On Querying Incomplete Information in Databases under Bag Semantics.
Temporal Sequences of Qualitative Information: Reasoning about the Topology of Constant-Size Moving Regions.
Inferring Implicit Event Locations from Context with Distributional Similarities.
Handling non-local dead-ends in Agent Planning Programs.
Discriminative Dictionary Learning With Ranking Metric Embedded for Person Re-Identification.
Learning from Ontology Streams with Semantic Concept Drift.
Most Probable Explanations for Probabilistic Database Queries.
Query Answering in Ontologies under Preference Rankings.
An Algorithm for Constructing and Solving Imperfect Recall Abstractions of Large Extensive-Form Games.
Belief Change in a Preferential Non-monotonic Framework.
Restricted Chase (Non)Termination for Existential Rules with Disjunctions.
Budget-Constrained Dynamics in Multiagent Systems.
Classical Generalized Probabilistic Satisfiability.
Strong Inconsistency in Nonmonotonic Reasoning.
Manipulating Opinion Diffusion in Social Networks.
On Coalitional Manipulation for Multiwinner Elections: Shortlisting.
Making Cross Products and Guarded Ontology Languages Compatible.
Generalized Planning: Non-Deterministic Abstractions and Trajectory Constraints.
Semantics for Active Integrity Constraints Using Approximation Fixpoint Theory.
Safe Inductions: An Algebraic Study.
The Impact of Treewidth on ASP Grounding and Solving.
Ontology-Mediated Query Answering for Key-Value Stores.
Reformulating Queries: Theory and Practice.
Reasoning about Probabilities in Unbounded First-Order Dynamical Domains.
Dynamic Logic for Data-aware Systems: Decidability Results.
A Model for Accountable Ordinal Sorting.
A Study of Unrestricted Abstract Argumentation Frameworks.
A General Notion of Equivalence for Abstract Argumentation.
Answering Conjunctive Regular Path Queries over Guarded Existential Rules.
Query Rewriting for DL-Lite with n-ary Concrete Domains.
Weakening Covert Networks by Minimizing Inverse Geodesic Length.
Epistemic-entrenchment Characterization of Parikh's Axiom.
On the Computational Complexity of Gossip Protocols.
Player Movement Models for Video Game Level Generation.
Nonlinear Hybrid Planning with Deep Net Learned Transition Models and Mixed-Integer Linear Programming.
Temporal Planning with Clock-Based SMT Encodings.
On Neighborhood Singleton Consistencies.
Constraint Games revisited.
Efficient Weighted Model Integration via SMT-Based Predicate Abstraction.
A Partitioning Algorithm for Maximum Common Subgraph Problems.
An Effective Learnt Clause Minimization Approach for CDCL SAT Solvers.
Enhancing Campaign Design in Crowdfunding: A Product Supply Optimization Perspective.
Solving Stochastic Boolean Satisfiability under Random-Exist Quantification.
Automatic Synthesis of Smart Table Constraints by Abstraction of Table Constraints.
A Recursive Shortcut for CEGAR: Application To The Modal Logic K Satisfiability Problem.
An Improved Decision-DNNF Compiler.
Learning to Run Heuristics in Tree Search.
Cardinality Encodings for Graph Optimization Problems.
A Core-Guided Approach to Learning Optimal Causal Graphs.
Locality in Random SAT Instances.
Finding Robust Solutions to Stable Marriage.
Restart and Random Walk in Local Search for Maximum Vertex Weight Cliques with Evaluations in Clustering Aggregation.
Personnel Scheduling as Satisfiability Modulo Theories.
Solving Integer Linear Programs with a Small Number of Global Variables and Constraints.
The Hard Problems Are Almost Everywhere For Random CNF-XOR Formulas.
Learning-Based Abstractions for Nonlinear Constraint Solving.
The DNA Word Design Problem: A New Constraint Model and New Results.
On the Kernelization of Global Constraints.
From Decimation to Local Search and Back: A New Approach to MaxSAT.
Relaxed Exists-Step Plans in Planning as SMT.
Compact MDDs for Pseudo-Boolean Constraints with At-Most-One Relations in Resource-Constrained Scheduling Problems.
Scalable Constraint-based Virtual Data Center Allocation.
Stochastic Constraint Programming with And-Or Branch-and-Bound.
Generating Hard Random Boolean Formulas and Disjunctive Logic Programs.
The Mixing of Markov Chains on Linear Extensions in Practice.
A Reduction based Method for Coloring Very Large Graphs.
Online Bridged Pruning for Real-Time Search with Arbitrary Lookaheads.
A Random Model for Argumentation Framework: Phase Transitions, Empirical Hardness, and Heuristics.
Compromise-free Pathfinding on a Navigation Mesh.
Front-to-End Bidirectional Heuristic Search with Near-Optimal Node Expansions.
An Admissible HTN Planning Heuristic.
Estimating the size of search trees by sampling with domain knowledge.
How to Form Winning Coalitions in Mixed Human-Computer Settings.
Agent Design Consistency Checking via Planning.
Score Aggregation via Spectral Method.
Multi-Agent Planning with Baseline Regret Minimization.
Manipulating Gale-Shapley Algorithm: Preserving Stability and Remaining Inconspicuous.
On the Power and Limitations of Deception in Multi-Robot Adversarial Patrolling.
Online Optimization of Video-Ad Allocation.
Attachment Centrality for Weighted Graphs.
Proportional Rankings.
Synchronisation Games on Hypergraphs.
Why You Should Charge Your Friends for Borrowing Your Stuff.
Posted Pricing sans Discrimination.
Don't Bury your Head in Warnings: A Game-Theoretic Approach for Intelligent Allocation of Cyber-security Alerts.
Enhancing Sustainability of Complex Epidemiological Models through a Generic Multilevel Agent-based Approach.
Multiple-Profile Prediction-of-Use Games.
Core Stability in Hedonic Games among Friends and Enemies: Impact of Neutrals.
Deterministic, Strategyproof, and Fair Cake Cutting.
Mechanisms for Online Organ Matching.
Computing an Approximately Optimal Agreeable Set of Items.
Probability Bounds for Overlapping Coalition Formation.
Recognizing Top-Monotonic Preference Profiles in Polynomial Time.
Crowd Learning: Improving Online Decision Making Using Crowdsourced Data.
Representativeness-aware Aspect Analysis for Brand Monitoring in Social Media.
Contest Design with Uncertain Performance and Costly Participation.
Smoothing Method for Approximate Extensive-Form Perfect Equilibrium.
Verifying Fault-tolerance in Parameterised Multi-Agent Systems.
Constraint-Based Symmetry Detection in General Game Playing.
Convergence and Quality of Iterative Voting Under Non-Scoring Rules.
Omniscient Debugging for Cognitive Agent Programs.
Tosca: Operationalizing Commitments Over Information Protocols.
A Bayesian Approach to Argument-Based Reasoning for Attack Estimation.
Near-Feasible Stable Matchings with Budget Constraints.
Online Roommate Allocation Problem.
Optimal Posted-Price Mechanism in Microtask Crowdsourcing.
The Off-Switch Game.
Object Allocation via Swaps along a Social Network.
A Novel Symbolic Approach to Verifying Epistemic Properties of Programs.
Operation Frames and Clubs in Kidney Exchange.
Multiwinner Rules on Paths From k-Borda to Chamberlin-Courant.
Interaction-based ontology alignment repair with expansion and relaxation.
No Pizza for You: Value-based Plan Selection in BDI Agents.
Pessimistic Leader-Follower Equilibria with Multiple Followers.
Coordinated Versus Decentralized Exploration In Multi-Agent Multi-Armed Bandits.
Plan Explanations as Model Reconciliation: Moving Beyond Explanation as Soliloquy.
Learning a Ground Truth Ranking Using Noisy Approval Votes.
Bounding the Inefficiency of Compromise.
Fair Division of a Graph.
Voting by sequential elimination with few voters.
Computing Bayes-Nash Equilibria in Combinatorial Auctions with Continuous Value and Action Spaces.
Aggressive, Tense or Shy? Identifying Personality Traits from Crowd Videos.
Equilibria in Ordinal Games: A Framework based on Possibility Theory.
Parameterised Verification of Data-aware Multi-Agent Systems.
Verification of Broadcasting Multi-Agent Systems against an Epistemic Strategy Logic.
The Condorcet Principle for Multiwinner Elections: From Shortlisting to Proportionality.
Pareto Optimal Allocation under Uncertain Preferences.
An Abstraction-Refinement Methodology for Reasoning about Network Games.
Measuring the Intensity of Attacks in Argumentation Graphs with Shapley Value.
Acceptability Semantics for Weighted Argumentation Frameworks.
Efficient Computation of Extensions for Dynamic Abstract Argumentation Frameworks: An Incremental Approach.
Pure Nash Equilibria in Online Fair Division.
Diverse Weighted Bipartite b-Matching.
Proactive and Reactive Coordination of Non-dedicated Agent Teams Operating in Uncertain Environments.
Super-Human AI for Strategic Reasoning: Beating Top Pros in Heads-Up No-Limit Texas Hold'em.
From Automation to Autonomous Systems: A Legal Phenomenology with Problems of Accountability.
Deep Learning at Alibaba.
Swift Logic for Big Data and Knowledge Graphs.