ijcai 2018 论文列表
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, IJCAI 2018, July 13-19, 2018, Stockholm, Sweden.
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Curly: An AI-based Curling Robot Successfully Competing in the Olympic Discipline of Curling.
Using a Deep Learning Dialogue Research Toolkit in a Multilingual Multidomain Practical Application.
Automated Reasoning for City Infrastructure Maintenance Decision Support.
Readitopics: Make Your Topic Models Readable via Labeling and Browsing.
Medusa: Towards Simulating a Multi-Agent Hide-and-Seek Game.
Glass-Box: Explaining AI Decisions With Counterfactual Statements Through Conversation With a Voice-enabled Virtual Assistant.
IBM Scenario Planning Advisor: Plan Recognition as AI Planning in Practice.
A Virtual Environment with Multi-Robot Navigation, Analytics, and Decision Support for Critical Incident Investigation.
Hintikka's World: Agents with Higher-order Knowledge.
Data-Driven Inventory Management and Dynamic Pricing Competition on Online Marketplaces.
Extracting Latent Beliefs and using Epistemic Reasoning to Tailor a Chatbot.
Multi-Sensor Mobile Platform for the Recognition of Activities of Daily Living and their Environments based on Artificial Neural Networks.
Semantic Representation of Data Science Programs.
Aesop: A Visual Storytelling Platform for Conversational AI.
Digitalized Cognitive Assessment mediated by a Virtual Caregiver.
A Wearable Device for Online and Long-Term ECG Monitoring.
Balanced News Using Constrained Bandit-based Personalization.
CISA: Chinese Information Structure Analysis for Scientific Writing with Cross-lingual Adversarial Learning.
Solving Sudoku with Consistency: A Visual and Interactive Approach.
TuringBox: An Experimental Platform for the Evaluation of AI Systems.
Pyconstruct: Constraint Programming Meets Structured Prediction.
Visualizations for an Explainable Planning Agent.
SynKit: LTL Synthesis as a Service.
Near Real-Time Detection of Poachers from Drones in AirSim.
Generating Plans for Cooperative Connected UAVs.
Intelligent Assistant for Elderly.
Instructing Novice Users on How to Use Tools in DIY Projects.
Using Contextual Bandits with Behavioral Constraints for Constrained Online Movie Recommendation.
Repairing ASR output by Artificial Development and Ontology based Learning.
Hatebusters: A Web Application for Actively Reporting YouTube Hate Speech.
Algorithmic Social Intervention.
Machine Learning Approaches to Reduce Electrical Waste and Improve Power Grid Stability.
Learning and Communicating the Latent States of Human-Machine Collaboration.
Bringing Multi-agent Path Finding Closer to Reality.
Conversational Explanations of Machine Learning Predictions Through Class-contrastive Counterfactual Statements.
Optimal Multi-Attribute Decision Making in Social Choice Problems.
Deception.
Multi-Agent Election-Based Hyper-Heuristics.
Identifying Differences in Social Responsiveness among Preschoolers Interacting with or Watching Social Robots.
Connecting Low-Level Image Processing and High-Level Vision via Deep Learning.
Data-driven Onboard Scheduling for an Autonomous Observation Satellite.
Optimal Multi-robot Task Planning: from Synthesis to Execution (and Back).
Intelligent Decision Support for Human Team Planning.
Restricted Communication in Online Multi-Robot Exploration.
Learning Portable Symbolic Representations.
AI for Conservation: Aerial Monitoring to Learn and Plan against Illegal Actors.
Handling Uncertainty in Recommender Systems under the Belief Function Theory.
Probabilistic Machine Learning: Models, Algorithms and a Programming Library.
Engineering Graph Features via Network Functional Blocks.
Mining Streaming and Temporal Data: from Representation to Knowledge.
Towards Sample Efficient Reinforcement Learning.
Towards Improving the Expressivity and Scalability of Distributed Constraint Optimization Problems.
Artificial Argumentation for Humans.
Improving Reinforcement Learning with Human Input.
Advances and Challenges in Privacy Preserving Planning.
Partakable Technology.
Improving Data Management using Domain Knowledge.
Interactive Learning and Decision Making: Foundations, Insights & Challenges.
Natural Language Understanding: Instructions for (Present and Future) Use.
Formal Analysis of Deep Binarized Neural Networks.
Grounded Language Learning: Where Robotics and NLP Meet.
Towards Human-Engaged AI.
Mental Health Computing via Harvesting Social Media Data.
Reasoning about NP-complete Constraints.
Statistical Quality Control for Human Computation and Crowdsourcing.
Decision-Making Under Uncertainty in Multi-Agent and Multi-Robot Systems: Planning and Learning.
Learning Continuous Time Bayesian Networks in Non-stationary Domains.
Viewpoint: Artificial Intelligence and Labour.
Distributional Correspondence Indexing for Cross-Lingual and Cross-Domain Sentiment Classification (Extended Abstract).
Lightweight Random Indexing for Polylingual Text Classification (Extended Abstract).
Rademacher Complexity Bounds for a Penalized Multi-class Semi-supervised Algorithm (Extended Abstract).
Impossibility in Belief Merging (Extended Abstract).
Three-Valued Semantics for Hybrid MKNF Knowledge Bases Revisited (Extended Abstract).
Linear Satisfiability Preserving Assignments (Extended Abstract).
Visualisation and 'Diagnostic Classifiers' Reveal how Recurrent and Recursive Neural Networks Process Hierarchical Structure (Extended Abstract).
Constrained Coalition Formation on Valuation Structures: Formal Framework, Applications, and Islands of Tractability (Extended Abstract).
Complexity of n-Queens Completion (Extended Abstract).
Fact-Alternating Mutex Groups for Classical Planning (Extended Abstract).
Learning Explanatory Rules from Noisy Data (Extended Abstract).
Preference-Based Inconsistency Management in Multi-Context Systems (Extended Abstract).
Prime Implicate Generation in Equational Logic (extended abstract).
From Feature to Paradigm: Deep Learning in Machine Translation (Extended Abstract).
On the Equivalence between Assumption-Based Argumentation and Logic Programming (Extended Abstract).
Revisiting the Arcade Learning Environment: Evaluation Protocols and Open Problems for General Agents (Extended Abstract).
Enhancing Context Knowledge Repositories with Justifiable Exceptions (Extended Abstract).
Solving Multi-Agent Path Finding on Strongly Biconnected Digraphs (Extended Abstract).
On the Logical Properties of the Description Logic DL^N (Extended abstract).
A COP Model for Graph-Constrained Coalition Formation (Extended Abstract).
MCTS-Minimax Hybrids with State Evaluations (Extended Abstract).
Incentive-Compatible Mechanisms for Norm Monitoring in Open Multi-Agent Systems (Extended Abstract).
Affective Image Content Analysis: A Comprehensive Survey.
Building Ethics into Artificial Intelligence.
"Chitty-Chitty-Chat Bot": Deep Learning for Conversational AI.
Ontology-Based Data Access: A Survey.
Advancements in Dueling Bandits.
Stackelberg Security Games: Looking Beyond a Decade of Success.
Autonomously Reusing Knowledge in Multiagent Reinforcement Learning.
Event Coreference Resolution: A Survey of Two Decades of Research.
Boosting Combinatorial Problem Modeling with Machine Learning.
Systems AI: A Declarative Learning Based Programming Perspective.
Maintenance of Case Bases: Current Algorithms after Fifty Years.
Evaluation Techniques and Systems for Answer Set Programming: a Survey.
AGI Safety Literature Review.
Robust Multi-view Representation: A Unified Perspective from Multi-view Learning to Domain Adaption.
Five Years of Argument Mining: a Data-driven Analysis.
Recent Advances in Querying Probabilistic Knowledge Bases.
Time Series Chains: A Novel Tool for Time Series Data Mining.
Modeling the Assimilation-Contrast Effects in Online Product Rating Systems: Debiasing and Recommendations.
A Conversational Approach to Process-oriented Case-based Reasoning.
Bridging the Gap Between Theory and Practice in Influence Maximization: Raising Awareness about HIV among Homeless Youth.
Greedy Stone Tower Creations with a Robotic Arm.
Generating High Resolution Climate Change Projections through Single Image Super-Resolution: An Abridged Version.
Operator Counting Heuristics for Probabilistic Planning.
Multi-Objective Optimization Through Pareto Minimal Correction Subsets.
Tamper-Proof Privacy Auditing for Artificial Intelligence Systems.
A Genetic Programming Approach to Designing Convolutional Neural Network Architectures.
Marathon Race Planning: A Case-Based Reasoning Approach.
An Efficient Minibatch Acceptance Test for Metropolis-Hastings.
Recursive Spoken Instruction-Based One-Shot Object and Action Learning.
Evaluating and Complementing Vision-to-Language Technology for People who are Blind with Conversational Crowdsourcing.
The Intricacies of Three-Valued Extensional Semantics for Higher-Order Logic Programs.
Completeness-aware Rule Learning from Knowledge Graphs.
Distributing Frank-Wolfe via Map-Reduce.
Cost-Based Goal Recognition for the Path-Planning Domain.
Inhibition of Occluded Facial Regions for Distance-Based Face Recognition.
An Empirical Study of Branching Heuristics through the Lens of Global Learning Rate.
Multi-Robot Motion Planning with Dynamics Guided by Multi-Agent Search.
Attributed Description Logics: Reasoning on Knowledge Graphs.
Counterexample-Driven Genetic Programming: Stochastic Synthesis of Provably Correct Programs.
Geolocating Images with Crowdsourcing and Diagramming.
Emergent Tangled Program Graphs in Multi-Task Learning.
Orchestrating a Network of Mereotopological Theories: An Abridged Report.
Unbiased Learning-to-Rank with Biased Feedback.
Make Evasion Harder: An Intelligent Android Malware Detection System.
Accelerating Innovation Through Analogy Mining.
Search Progress and Potentially Expanded States in Greedy Best-First Search.
Translation-based Recommendation: A Scalable Method for Modeling Sequential Behavior.
A Model of Distributed Query Computation in Client-Server Scenarios on the Semantic Web.
Toeplitz Inverse Covariance-based Clustering of Multivariate Time Series Data.
Reducing Controversy by Connecting Opposing Views.
Inductive Certificates of Unsolvability for Domain-Independent Planning.
Importance Sampling for Fair Policy Selection.
Combinatorial Cost Sharing.
The Finite Model Theory of Bayesian Networks: Descriptive Complexity.
Dynamic Dependency Awareness for QBF.
Learning with Sparse and Biased Feedback for Personal Search.
Improving Information Extraction from Images with Learned Semantic Models.
Reduced Cost Fixing for Maximum Satisfiability.
A Unifying View of Geometry, Semantics, and Data Association in SLAM.
TensorCast: Forecasting Time-Evolving Networks with Contextual Information.
Weighted Bipolar Argumentation Graphs: Axioms and Semantics.
Finite Controllability of Conjunctive Query Answering with Existential Rules: Two Steps Forward.
The Facets of Artificial Intelligence: A Framework to Track the Evolution of AI.
Evolving AI from Research to Real Life - Some Challenges and Suggestions.
Quantifying Algorithmic Improvements over Time.
Artificial Intelligence Conferences Closeness.
Towards Consumer-Empowering Artificial Intelligence.
On a Scientific Discipline (Once) Named AI.
A Savage-style Utility Theory for Belief Functions.
Mixed Causal Structure Discovery with Application to Prescriptive Pricing.
A Scalable Scheme for Counting Linear Extensions.
Scalable Probabilistic Causal Structure Discovery.
A Symbolic Approach to Explaining Bayesian Network Classifiers.
Algorithms for the Nearest Assignment Problem.
Reliable Multi-class Classification based on Pairwise Epistemic and Aleatoric Uncertainty.
Estimation with Incomplete Data: The Linear Case.
Stochastic Anytime Search for Bounding Marginal MAP.
Lifted Filtering via Exchangeable Decomposition.
Unsupervised Learning based Jump-Diffusion Process for Object Tracking in Video Surveillance.
Patent Litigation Prediction: A Convolutional Tensor Factorization Approach.
Building Sparse Deep Feedforward Networks using Tree Receptive Fields.
Policy Optimization with Second-Order Advantage Information.
Efficient Symbolic Integration for Probabilistic Inference.
A Graphical Criterion for Effect Identification in Equivalence Classes of Causal Diagrams.
Redundancy-resistant Generative Hashing for Image Retrieval.
Metadata-dependent Infinite Poisson Factorization for Efficiently Modelling Sparse and Large Matrices in Recommendation.
On Robust Trimming of Bayesian Network Classifiers.
The Promise and Perils of Myopia in Dynamic Pricing With Censored Information.
Efficient Localized Inference for Large Graphical Models.
Parameterised Queries and Lifted Query Answering.
Active Recurrence of Lighting Condition for Fine-Grained Change Detection.
Active Object Reconstruction Using a Guided View Planner.
3D-PhysNet: Learning the Intuitive Physics of Non-Rigid Object Deformations.
Behavioral Cloning from Observation.
Robot Task Interruption by Learning to Switch Among Multiple Models.
Learning Unmanned Aerial Vehicle Control for Autonomous Target Following.
An Appearance-and-Structure Fusion Network for Object Viewpoint Estimation.
Online, Interactive User Guidance for High-dimensional, Constrained Motion Planning.
Virtual-to-Real: Learning to Control in Visual Semantic Segmentation.
Interactive Robot Transition Repair With SMT.
Implicit Non-linear Similarity Scoring for Recognizing Unseen Classes.
Bayesian Active Edge Evaluation on Expensive Graphs.
Learning Transferable UAV for Forest Visual Perception.
GraspNet: An Efficient Convolutional Neural Network for Real-time Grasp Detection for Low-powered Devices.
Minimax-Regret Querying on Side Effects for Safe Optimality in Factored Markov Decision Processes.
PEORL: Integrating Symbolic Planning and Hierarchical Reinforcement Learning for Robust Decision-Making.
Admissible Abstractions for Near-optimal Task and Motion Planning.
Completeness-Preserving Dominance Techniques for Satisficing Planning.
LP Heuristics over Conjunctions: Compilation, Convergence, Nogood Learning.
Hierarchical Expertise Level Modeling for User Specific Contrastive Explanations.
Dynamic Resource Routing using Real-Time Dynamic Programming.
Planning in Factored State and Action Spaces with Learned Binarized Neural Network Transition Models.
Counterplanning using Goal Recognition and Landmarks.
Scalable Initial State Interdiction for Factored MDPs.
Organizing Experience: a Deeper Look at Replay Mechanisms for Sample-Based Planning in Continuous State Domains.
Effect-Abstraction Based Relaxation for Linear Numeric Planning.
Small Undecidable Problems in Epistemic Planning.
Learning to Infer Final Plans in Human Team Planning.
Goal-HSVI: Heuristic Search Value Iteration for Goal POMDPs.
Model Checking Probabilistic Epistemic Logic for Probabilistic Multiagent Systems.
Unchaining the Power of Partial Delete Relaxation, Part II: Finding Plans with Red-Black State Space Search.
Traffic Light Scheduling, Value of Time, and Incentives.
Complexity of Scheduling Charging in the Smart Grid.
Automata-Theoretic Foundations of FOND Planning for LTLf and LDLf Goals.
Emergency Response Optimization using Online Hybrid Planning.
Analyzing Tie-Breaking Strategies for the A* Algorithm.
Local Minima, Heavy Tails, and Search Effort for GBFS.
Computational Approaches for Stochastic Shortest Path on Succinct MDPs.
Expectation Optimization with Probabilistic Guarantees in POMDPs with Discounted-Sum Objectives.
LTL Realizability via Safety and Reachability Games.
Planning and Learning with Stochastic Action Sets.
Features, Projections, and Representation Change for Generalized Planning.
Variable-Delay Controllability.
Novel Structural Parameters for Acyclic Planning Using Tree Embeddings.
Scheduling under Uncertainty: A Query-based Approach.
Multi-modal Predicate Identification using Dynamically Learned Robot Controllers.
Differentiated Attentive Representation Learning for Sentence Classification.
Commonsense Knowledge Aware Conversation Generation with Graph Attention.
Same Representation, Different Attentions: Shareable Sentence Representation Learning from Multiple Tasks.
Phrase Table as Recommendation Memory for Neural Machine Translation.
Neural Networks Incorporating Unlabeled and Partially-labeled Data for Cross-domain Chinese Word Segmentation.
Text Emotion Distribution Learning via Multi-Task Convolutional Neural Network.
Towards Reading Comprehension for Long Documents.
Learning Tag Dependencies for Sequence Tagging.
Weakly Supervised Audio Source Separation via Spectrum Energy Preserved Wasserstein Learning.
Reinforcing Coherence for Sequence to Sequence Model in Dialogue Generation.
Biased Random Walk based Social Regularization for Word Embeddings.
Chinese Poetry Generation with a Working Memory Model.
Teaching Machines to Ask Questions.
Generating Thematic Chinese Poetry using Conditional Variational Autoencoders with Hybrid Decoders.
Ensemble Neural Relation Extraction with Adaptive Boosting.
Smarter Response with Proactive Suggestion: A New Generative Neural Conversation Paradigm.
Enhancing Semantic Representations of Bilingual Word Embeddings with Syntactic Dependencies.
Lifelong Domain Word Embedding via Meta-Learning.
Scheduled Policy Optimization for Natural Language Communication with Intelligent Agents.
Transformable Convolutional Neural Network for Text Classification.
Instance Weighting with Applications to Cross-domain Text Classification via Trading off Sample Selection Bias and Variance.
Quality Matters: Assessing cQA Pair Quality via Transductive Multi-View Learning.
Transition-based Adversarial Network for Cross-lingual Aspect Extraction.
Densely Connected CNN with Multi-scale Feature Attention for Text Classification.
Joint Extraction of Entities and Relations Based on a Novel Graph Scheme.
A Reinforced Topic-Aware Convolutional Sequence-to-Sequence Model for Abstractive Text Summarization.
SentiGAN: Generating Sentimental Texts via Mixture Adversarial Networks.
Aspect Sentiment Classification with both Word-level and Clause-level Attention Networks.
One "Ruler" for All Languages: Multi-Lingual Dialogue Evaluation with Adversarial Multi-Task Learning.
Hermitian Co-Attention Networks for Text Matching in Asymmetrical Domains.
Get The Point of My Utterance! Learning Towards Effective Responses with Multi-Head Attention Mechanism.
Multiway Attention Networks for Modeling Sentence Pairs.
A Weakly Supervised Method for Topic Segmentation and Labeling in Goal-oriented Dialogues via Reinforcement Learning.
Bootstrapping Entity Alignment with Knowledge Graph Embedding.
Exploring Encoder-Decoder Model for Distant Supervised Relation Extraction.
An Ensemble of Retrieval-Based and Generation-Based Human-Computer Conversation Systems.
Joint Learning Embeddings for Chinese Words and their Components via Ladder Structured Networks.
Complementary Learning of Word Embeddings.
Toward Diverse Text Generation with Inverse Reinforcement Learning.
Listen, Think and Listen Again: Capturing Top-down Auditory Attention for Speaker-independent Speech Separation.
Reinforced Self-Attention Network: a Hybrid of Hard and Soft Attention for Sequence Modeling.
Learning to Converse with Noisy Data: Generation with Calibration.
Functional Partitioning of Ontologies for Natural Language Query Completion in Question Answering Systems.
Interpretable Adversarial Perturbation in Input Embedding Space for Text.
Joint Posterior Revision of NLP Annotations via Ontological Knowledge.
Learning Out-of-Vocabulary Words in Intelligent Personal Agents.
Inferring Temporal Knowledge for Near-Periodic Recurrent Events.
Event Factuality Identification via Generative Adversarial Networks with Auxiliary Classification.
Translating Embeddings for Knowledge Graph Completion with Relation Attention Mechanism.
Assigning Personality/Profile to a Chatting Machine for Coherent Conversation Generation.
ElimiNet: A Model for Eliminating Options for Reading Comprehension with Multiple Choice Questions.
Answering Mixed Type Questions about Daily Living Episodes.
Show and Tell More: Topic-Oriented Multi-Sentence Image Captioning.
A Hierarchical End-to-End Model for Jointly Improving Text Summarization and Sentiment Classification.
Beyond Polarity: Interpretable Financial Sentiment Analysis with Hierarchical Query-driven Attention.
Jumper: Learning When to Make Classification Decision in Reading.
Learning to Explain Ambiguous Headlines of Online News.
Curriculum Learning for Natural Answer Generation.
Feature Enhancement in Attention for Visual Question Answering.
Deep Text Classification Can be Fooled.
Constructing Narrative Event Evolutionary Graph for Script Event Prediction.
Aspect Term Extraction with History Attention and Selective Transformation.
Learning Word Vectors with Linear Constraints: A Matrix Factorization Approach.
Non-translational Alignment for Multi-relational Networks.
Adaboost with Auto-Evaluation for Conversational Models.
SegBot: A Generic Neural Text Segmentation Model with Pointer Network.
Code Completion with Neural Attention and Pointer Networks.
Multi-modal Sentence Summarization with Modality Attention and Image Filtering.
An Adaptive Hierarchical Compositional Model for Phrase Embedding.
ACV-tree: A New Method for Sentence Similarity Modeling.
Learning to Give Feedback: Modeling Attributes Affecting Argument Persuasiveness in Student Essays.
Mitigating the Effect of Out-of-Vocabulary Entity Pairs in Matrix Factorization for KB Inference.
Goal-Oriented Chatbot Dialog Management Bootstrapping with Transfer Learning.
Improving Entity Recommendation with Search Log and Multi-Task Learning.
Reinforced Mnemonic Reader for Machine Reading Comprehension.
Approximating Word Ranking and Negative Sampling for Word Embedding.
EZLearn: Exploiting Organic Supervision in Automated Data Annotation.
Topic-to-Essay Generation with Neural Networks.
Improving Low Resource Named Entity Recognition using Cross-lingual Knowledge Transfer.
Extracting Action Sequences from Texts Based on Deep Reinforcement Learning.
Efficient Pruning of Large Knowledge Graphs.
A Question Type Driven Framework to Diversify Visual Question Generation.
A Deep Modular RNN Approach for Ethos Mining.
Attention-Fused Deep Matching Network for Natural Language Inference.
Domain Adaptation via Tree Kernel Based Maximum Mean Discrepancy for User Consumption Intention Identification.
Submodularity-Inspired Data Selection for Goal-Oriented Chatbot Training Based on Sentence Embeddings.
Adversarial Active Learning for Sequences Labeling and Generation.
TreeNet: Learning Sentence Representations with Unconstrained Tree Structure.
Co-training Embeddings of Knowledge Graphs and Entity Descriptions for Cross-lingual Entity Alignment.
Point Set Registration for Unsupervised Bilingual Lexicon Induction.
Medical Concept Embedding with Time-Aware Attention.
An Encoder-Decoder Framework Translating Natural Language to Database Queries.
Think Globally, Embed Locally - Locally Linear Meta-embedding of Words.
Empirical Analysis of Foundational Distinctions in Linked Open Data.
Translations as Additional Contexts for Sentence Classification.
A Brand-level Ranking System with the Customized Attention-GRU Model.
Impression Allocation for Combating Fraud in E-commerce Via Deep Reinforcement Learning with Action Norm Penalty.
GELU-Net: A Globally Encrypted, Locally Unencrypted Deep Neural Network for Privacy-Preserved Learning.
Sequential Recommender System based on Hierarchical Attention Networks.
Representing Urban Functions through Zone Embedding with Human Mobility Patterns.
From the Periphery to the Core: Information Brokerage in an Evolving Network.
Generating Adversarial Examples with Adversarial Networks.
Axiomatization of the PageRank Centrality.
Cascaded SR-GAN for Scale-Adaptive Low Resolution Person Re-identification.
High-Fidelity Simulated Players for Interactive Narrative Planning.
Exploiting POI-Specific Geographical Influence for Point-of-Interest Recommendation.
A Group-based Approach to Improve Multifactorial Evolutionary Algorithm.
MASTER: across Multiple social networks, integrate Attribute and STructure Embedding for Reconciliation.
Path Evaluation and Centralities in Weighted Graphs - An Axiomatic Approach.
Optimal Cruiser-Drone Traffic Enforcement Under Energy Limitation.
Weakly Learning to Match Experts in Online Community.
Neural User Response Generator: Fake News Detection with Collective User Intelligence.
LSTM Networks for Online Cross-Network Recommendations.
DyNMF: Role Analytics in Dynamic Social Networks.
A Non-Parametric Generative Model for Human Trajectories.
Towards Better Representation Learning for Personalized News Recommendation: a Multi-Channel Deep Fusion Approach.
Social Media based Simulation Models for Understanding Disease Dynamics.
A Social Interaction Activity based Time-Varying User Vectorization Method for Online Social Networks.
Adversarial Task Assignment.
Tag-based Weakly-supervised Hashing for Image Retrieval.
Adversarial Regression for Detecting Attacks in Cyber-Physical Systems.
Three-Head Neural Network Architecture for Monte Carlo Tree Search.
Fact Checking via Evidence Patterns.
A^3NCF: An Adaptive Aspect Attention Model for Rating Prediction.
Curriculum Adversarial Training.
Periodic-CRN: A Convolutional Recurrent Model for Crowd Density Prediction with Recurring Periodic Patterns.
Globally Optimized Mutual Influence Aware Ranking in E-Commerce Search.
A Local Algorithm for Product Return Prediction in E-Commerce.
A Deep Framework for Cross-Domain and Cross-System Recommendations.
JUMP: a Jointly Predictor for User Click and Dwell Time.
Fast Vehicle Identification in Surveillance via Ranked Semantic Sampling Based Embedding.
Multi-Turn Video Question Answering via Multi-Stream Hierarchical Attention Context Network.
Open-Ended Long-form Video Question Answering via Adaptive Hierarchical Reinforced Networks.
PLASTIC: Prioritize Long and Short-term Information in Top-n Recommendation using Adversarial Training.
NeuRec: On Nonlinear Transformation for Personalized Ranking.
CoupledCF: Learning Explicit and Implicit User-item Couplings in Recommendation for Deep Collaborative Filtering.
DeepTravel: a Neural Network Based Travel Time Estimation Model with Auxiliary Supervision.
Finding Communities with Hierarchical Semantics by Distinguishing General and Specialized topics.
Task-Guided and Semantic-Aware Ranking for Academic Author-Paper Correlation Inference.
Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting.
Joint Learning of Phenotypes and Diagnosis-Medication Correspondence via Hidden Interaction Tensor Factorization.
Biharmonic Distance Related Centrality for Edges in Weighted Networks.
3-in-1 Correlated Embedding via Adaptive Exploration of the Structure and Semantic Subspaces.
Line separation from topographic maps using regional color and spatial information.
Extracting Job Title Hierarchy from Career Trajectories: A Bayesian Perspective.
Where Have You Been? Inferring Career Trajectory from Academic Social Network.
Matrix completion with Preference Ranking for Top-N Recommendation.
Predicting the Spatio-Temporal Evolution of Chronic Diseases in Population with Human Mobility Data.
Real-time Traffic Pattern Analysis and Inference with Sparse Video Surveillance Information.
Power-law Distribution Aware Trust Prediction.
Estimating Latent People Flow without Tracking Individuals.
Discrete Network Embedding.
A Joint Learning Approach to Intelligent Job Interview Assessment.
Improving Information Centrality of a Node in Complex Networks by Adding Edges.
Hybrid Approach of Relation Network and Localized Graph Convolutional Filtering for Breast Cancer Subtype Classification.
Pairwise-Ranking based Collaborative Recurrent Neural Networks for Clinical Event Prediction.
ANOMALOUS: A Joint Modeling Approach for Anomaly Detection on Attributed Networks.
Hierarchical Electricity Time Series Forecasting for Integrating Consumption Patterns Analysis and Aggregation Consistency.
On Whom Should I Perform this Lab Test Next? An Active Feature Elicitation Approach.
From Reality to Perception: Genre-Based Neural Image Style Transfer.
Your Tweets Reveal What You Like: Introducing Cross-media Content Information into Multi-domain Recommendation.
Drug Similarity Integration Through Attentive Multi-view Graph Auto-Encoders.
LC-RNN: A Deep Learning Model for Traffic Speed Prediction.
Dynamic Bayesian Logistic Matrix Factorization for Recommendation with Implicit Feedback.
Hashtag2Vec: Learning Hashtag Representation with Relational Hierarchical Embedding Model.
Discrete Factorization Machines for Fast Feature-based Recommendation.
Deep Reinforcement Learning in Ice Hockey for Context-Aware Player Evaluation.
Predicting Activity and Location with Multi-task Context Aware Recurrent Neural Network.
GeoMAN: Multi-level Attention Networks for Geo-sensory Time Series Prediction.
Lightweight Label Propagation for Large-Scale Network Data.
Modeling Contemporaneous Basket Sequences with Twin Networks for Next-Item Recommendation.
Integrative Network Embedding via Deep Joint Reconstruction.
Interpretable Recommendation via Attraction Modeling: Learning Multilevel Attractiveness over Multimodal Movie Contents.
Aspect-Level Deep Collaborative Filtering via Heterogeneous Information Networks.
Discrete Interventions in Hawkes Processes with Applications in Invasive Species Management.
Recommendation with Multi-Source Heterogeneous Information.
Interpretable Drug Target Prediction Using Deep Neural Representation.
Deep Attributed Network Embedding.
Automatic Opioid User Detection from Twitter: Transductive Ensemble Built on Different Meta-graph Based Similarities over Heterogeneous Information Network.
Recurrent Collaborative Filtering for Unifying General and Sequential Recommender.
Improving Implicit Recommender Systems with View Data.
Learning to Recognize Transient Sound Events using Attentional Supervision.
DELF: A Dual-Embedding based Deep Latent Factor Model for Recommendation.
Predicting Complex Activities from Ongoing Multivariate Time Series.
NeuCast: Seasonal Neural Forecast of Power Grid Time Series.
Beyond the Click-Through Rate: Web Link Selection with Multi-level Feedback.
Content-Aware Hierarchical Point-of-Interest Embedding Model for Successive POI Recommendation.
A Fast and Accurate Method for Estimating People Flow from Spatiotemporal Population Data.
Sampling for Approximate Bipartite Network Projection.
Robust Multi-view Learning via Half-quadratic Minimization.
Localized Incomplete Multiple Kernel k-means.
Improving Deep Neural Network Sparsity through Decorrelation Regularization.
Robust Graph Dimensionality Reduction.
Fast Model Identification via Physics Engines for Data-Efficient Policy Search.
Beyond Similar and Dissimilar Relations : A Kernel Regression Formulation for Metric Learning.
Towards Generalized and Efficient Metric Learning on Riemannian Manifold.
Cost-aware Cascading Bandits.
On the Convergence Properties of a K-step Averaging Stochastic Gradient Descent Algorithm for Nonconvex Optimization.
Trajectory-User Linking via Variational AutoEncoder.
Where to Prune: Using LSTM to Guide End-to-end Pruning.
Self-Adaptive Double Bootstrapped DDPG.
Robust Feature Selection on Incomplete Data.
Attentional Image Retweet Modeling via Multi-Faceted Ranking Network Learning.
Grouping Attribute Recognition for Pedestrian with Joint Recurrent Learning.
Deep Convolutional Neural Networks with Merge-and-Run Mappings.
Dynamic Hypergraph Structure Learning.
ANRL: Attributed Network Representation Learning via Deep Neural Networks.
Distributed Self-Paced Learning in Alternating Direction Method of Multipliers.
Self-Supervised Deep Low-Rank Assignment Model for Prototype Selection.
Multi-Task Clustering with Model Relation Learning.
Label-Sensitive Task Grouping by Bayesian Nonparametric Approach for Multi-Task Multi-Label Learning.
Online Kernel Selection via Incremental Sketched Kernel Alignment.
Multi-modality Sensor Data Classification with Selective Attention.
Semi-Supervised Optimal Margin Distribution Machines.
Achieving Non-Discrimination in Prediction.
Dynamically Hierarchy Revolution: DirNet for Compressing Recurrent Neural Network on Mobile Devices.
Scalable Multiplex Network Embedding.
Generative Warfare Nets: Ensemble via Adversaries and Collaborators.
Learning to Design Games: Strategic Environments in Reinforcement Learning.
Learning Environmental Calibration Actions for Policy Self-Evolution.
FISH-MML: Fisher-HSIC Multi-View Metric Learning.
Mixture of GANs for Clustering.
A Generic Approach for Accelerating Stochastic Zeroth-Order Convex Optimization.
Request-and-Reverify: Hierarchical Hypothesis Testing for Concept Drift Detection with Expensive Labels.
Hashing over Predicted Future Frames for Informed Exploration of Deep Reinforcement Learning.
Stochastic Fractional Hamiltonian Monte Carlo.
Distance Metric Facilitated Transportation between Heterogeneous Domains.
High-dimensional Similarity Learning via Dual-sparse Random Projection.
Semi-Supervised Multi-Modal Learning with Incomplete Modalities.
Bandit Online Learning on Graphs via Adaptive Optimization.
A Unified Approach for Multi-step Temporal-Difference Learning with Eligibility Traces in Reinforcement Learning.
Spatio-Temporal Check-in Time Prediction with Recurrent Neural Network based Survival Analysis.
Semi-Supervised Optimal Transport for Heterogeneous Domain Adaptation.
Cost-Effective Active Learning for Hierarchical Multi-Label Classification.
A Unified Analysis of Stochastic Momentum Methods for Deep Learning.
Improving Maximum Likelihood Estimation of Temporal Point Process via Discriminative and Adversarial Learning.
PredCNN: Predictive Learning with Cascade Convolutions.
Convergence Analysis of Gradient Descent for Eigenvector Computation.
Label Enhancement for Label Distribution Learning.
Multi-Level Metric Learning via Smoothed Wasserstein Distance.
MUSCAT: Multi-Scale Spatio-Temporal Learning with Application to Climate Modeling.
Online Continuous-Time Tensor Factorization Based on Pairwise Interactive Point Processes.
Deep Multi-View Concept Learning.
De-biasing Covariance-Regularized Discriminant Analysis.
Multi-Label Co-Training.
Cutting the Software Building Efforts in Continuous Integration by Semi-Supervised Online AUC Optimization.
Towards Enabling Binary Decomposition for Partial Label Learning.
Efficient Attributed Network Embedding via Recursive Randomized Hashing.
Unsupervised Deep Hashing via Binary Latent Factor Models for Large-scale Cross-modal Retrieval.
Does Tail Label Help for Large-Scale Multi-Label Learning.
Positive and Unlabeled Learning for Detecting Software Functional Clones with Adversarial Training.
Fast Factorization-free Kernel Learning for Unlabeled Chunk Data Streams.
New Balanced Active Learning Model and Optimization Algorithm.
Mixed Link Networks.
Feature Hashing for Network Representation Learning.
Iterative Metric Learning for Imbalance Data Classification.
Adaptive Graph Guided Embedding for Multi-label Annotation.
Convolutional Memory Blocks for Depth Data Representation Learning.
Binary Coding based Label Distribution Learning.
Ranking Preserving Nonnegative Matrix Factorization.
Progressive Blockwise Knowledge Distillation for Neural Network Acceleration.
Minimizing Adaptive Regret with One Gradient per Iteration.
Cascaded Low Rank and Sparse Representation on Grassmann Manifolds.
Efficient Adaptive Online Learning via Frequent Directions.
Deterministic Binary Filters for Convolutional Neural Networks.
Differentiable Submodular Maximization.
Deep into Hypersphere: Robust and Unsupervised Anomaly Discovery in Dynamic Networks.
Algorithms or Actions? A Study in Large-Scale Reinforcement Learning.
Exploration by Distributional Reinforcement Learning.
Incomplete Multi-View Weak-Label Learning.
Student-t Variational Autoencoder for Robust Density Estimation.
Positive and Unlabeled Learning via Loss Decomposition and Centroid Estimation.
Refine or Represent: Residual Networks with Explicit Channel-wise Configuration.
Deep Discrete Prototype Multilabel Learning.
A Bayesian Latent Variable Model of User Preferences with Item Context.
Online Deep Learning: Learning Deep Neural Networks on the Fly.
Reachability Analysis of Deep Neural Networks with Provable Guarantees.
Robust Auto-Weighted Multi-View Clustering.
Adversarial Constraint Learning for Structured Prediction.
Cross-modal Bidirectional Translation via Reinforcement Learning.
Label Embedding Based on Multi-Scale Locality Preservation.
Generalization-Aware Structured Regression towards Balancing Bias and Variance.
Adversarially Regularized Graph Autoencoder for Graph Embedding.
Multinomial Logit Bandit with Linear Utility Functions.
A Degeneracy Framework for Graph Similarity.
CAGAN: Consistent Adversarial Training Enhanced GANs.
An Information Theory based Approach to Multisource Clustering.
Neural Machine Translation with Key-Value Memory-Augmented Attention.
Interactive Optimal Teaching with Unknown Learners.
Spectral Feature Scaling Method for Supervised Dimensionality Reduction.
Unpaired Multi-Domain Image Generation via Regularized Conditional GANs.
On Q-learning Convergence for Non-Markov Decision Processes.
Self-Representative Manifold Concept Factorization with Adaptive Neighbors for Clustering.
Hierarchical Active Learning with Group Proportion Feedback.
Online Heterogeneous Transfer Metric Learning.
SDMCH: Supervised Discrete Manifold-Embedded Cross-Modal Hashing.
AAR-CNNs: Auto Adaptive Regularized Convolutional Neural Networks.
Exact Low Tubal Rank Tensor Recovery from Gaussian Measurements.
Fast Cross-Validation.
Zero Shot Learning via Low-rank Embedded Semantic AutoEncoder.
Learning with Adaptive Neighbors for Image Clustering.
Exploiting Graph Regularized Multi-dimensional Hawkes Processes for Modeling Events with Spatio-temporal Characteristics.
Toward Designing Convergent Deep Operator Splitting Methods for Task-specific Nonconvex Optimization.
Contextual Outlier Interpretation.
High-Order Co-Clustering via Strictly Orthogonal and Symmetric L1-Norm Nonnegative Matrix Tri-Factorization.
Structured Inference for Recurrent Hidden Semi-markov Model.
UCBoost: A Boosting Approach to Tame Complexity and Optimality for Stochastic Bandits.
Episodic Memory Deep Q-Networks.
Accelerating Convolutional Networks via Global & Dynamic Filter Pruning.
Unsupervised Disentangled Representation Learning with Analogical Relations.
R-SVM+: Robust Learning with Privileged Information.
Variance Reduction in Black-box Variational Inference by Adaptive Importance Sampling.
Deep Joint Semantic-Embedding Hashing.
Finite Sample Analysis of LSTD with Random Projections and Eligibility Traces.
Optimization based Layer-wise Magnitude-based Pruning for DNN Compression.
Generalization Bounds for Regularized Pairwise Learning.
Z-Transforms and its Inference on Partially Observable Point Processes.
Open Loop Execution of Tree-Search Algorithms.
Geometric Enclosing Networks.
A Property Testing Framework for the Theoretical Expressivity of Graph Kernels.
HST-LSTM: A Hierarchical Spatial-Temporal Long-Short Term Memory Network for Location Prediction.
Learning SMT(LRA) Constraints using SMT Solvers.
Temporal Belief Memory: Imputing Missing Data during RNN Training.
Network Approximation using Tensor Sketching.
Self-weighted Multiple Kernel Learning for Graph-based Clustering and Semi-supervised Classification.
Automatic Gating of Attributes in Deep Structure.
Efficient DNN Neuron Pruning by Minimizing Layer-wise Nonlinear Reconstruction Error.
Combinatorial Pure Exploration with Continuous and Separable Reward Functions and Its Applications.
A Normalized Convolutional Neural Network for Guided Sparse Depth Upsampling.
Experienced Optimization with Reusable Directional Model for Hyper-Parameter Search.
Summarizing Source Code with Transferred API Knowledge.
Doubly Aligned Incomplete Multi-view Clustering.
Generative Adversarial Positive-Unlabelled Learning.
Preventing Disparate Treatment in Sequential Decision Making.
Time-evolving Text Classification with Deep Neural Networks.
Soft Filter Pruning for Accelerating Deep Convolutional Neural Networks.
Outer Product-based Neural Collaborative Filtering.
Differential Equations for Modeling Asynchronous Algorithms.
MIXGAN: Learning Concepts from Different Domains for Mixture Generation.
Replicating Active Appearance Model by Generator Network.
Experimental Design under the Bradley-Terry Model.
INITIATOR: Noise-contrastive Estimation for Marked Temporal Point Process.
Energy-efficient Amortized Inference with Cascaded Deep Classifiers.
Regularizing Deep Neural Networks with an Ensemble-based Decorrelation Method.
Accelerated Asynchronous Greedy Coordinate Descent Algorithm for SVMs.
Faster Training Algorithms for Structured Sparsity-Inducing Norm.
Teaching Semi-Supervised Classifier via Generalized Distillation.
Scalable Rule Learning via Learning Representation.
Active Discriminative Network Representation Learning.
Cuckoo Feature Hashing: Dynamic Weight Sharing for Sparse Analytics.
Stochastic Second-Order Method for Large-Scale Nonconvex Sparse Learning Models.
Joint Generative Moment-Matching Network for Learning Structural Latent Code.
Complementary Binary Quantization for Joint Multiple Indexing.
Leveraging Latent Label Distributions for Partial Label Learning.
A Novel Data Representation for Effective Learning in Class Imbalanced Scenarios.
Quantum Divide-and-Conquer Anchoring for Separable Non-negative Matrix Factorization.
Dynamic Network Embedding : An Extended Approach for Skip-gram based Network Embedding.
Galaxy Network Embedding: A Hierarchical Community Structure Preserving Approach.
Counterexample-Guided Data Augmentation.
Adaptive Collaborative Similarity Learning for Unsupervised Multi-view Feature Selection.
Behavior of Analogical Inference w.r.t. Boolean Functions.
Unifying and Merging Well-trained Deep Neural Networks for Inference Stage.
Causal Inference in Time Series via Supervised Learning.
Solving Separable Nonsmooth Problems Using Frank-Wolfe with Uniform Affine Approximations.
Distributed Primal-Dual Optimization for Non-uniformly Distributed Data.
Adversarial Metric Learning.
Tri-net for Semi-Supervised Deep Learning.
Convolutional Neural Networks based Click-Through Rate Prediction with Multiple Feature Sequences.
Small-Variance Asymptotics for Nonparametric Bayesian Overlapping Stochastic Blockmodels.
Finding Frequent Entities in Continuous Data.
On Concept Forgetting in Description Logics with Qualified Number Restrictions.
Inconsistency Measures for Repair Semantics in OBDA.
Consequence-based Reasoning for Description Logics with Disjunction, Inverse Roles, Number Restrictions, and Nominals.
Reasoning about Betweenness and RCC8 Constraints in Qualitative Conceptual Spaces.
Abducing Relations in Continuous Spaces.
Argumentation-Based Recommendations: Fantastic Explanations and How to Find Them.
Two Approaches to Ontology Aggregation Based on Axiom Weakening.
Leveraging Qualitative Reasoning to Improve SFL.
Incrementally Grounding Expressions for Spatial Relations between Objects.
Complexity of Approximate Query Answering under Inconsistency in Datalog+/-.
Multi-agent Epistemic Planning with Common Knowledge.
Novel Algorithms for Abstract Dialectical Frameworks based on Complexity Analysis of Subclasses and SAT Solving.
An Efficient Algorithm To Compute Distance Between Lexicographic Preference Trees.
Pseudo-Boolean Constraints from a Knowledge Representation Perspective.
Counterfactual Resimulation for Causal Analysis of Rule-Based Models.
Stratified Negation in Limit Datalog Programs.
On the Conditional Logic of Simulation Models.
Horn-Rewritability vs PTime Query Evaluation in Ontology-Mediated Querying.
Two Sides of the Same Coin: Belief Revision and Enforcing Arguments.
Reverse Engineering Queries in Ontology-Enriched Systems: The Case of Expressive Horn Description Logic Ontologies.
Computing Approximate Query Answers over Inconsistent Knowledge Bases.
Finite Model Reasoning in Hybrid Classes of Existential Rules.
Possibilistic ASP Base Revision by Certain Input.
An Empirical Study of Knowledge Tradeoffs in Case-Based Reasoning.
From Conjunctive Queries to Instance Queries in Ontology-Mediated Querying.
Probabilistic bipolar abstract argumentation frameworks: complexity results.
Game Description Language and Dynamic Epistemic Logic Compared.
A Study of Argumentative Characterisations of Preferred Subtheories.
Belief Update in the Horn Fragment.
The Complexity of Limited Belief Reasoning - The Quantifier-Free Case.
Embracing Change by Abstraction Materialization Maintenance for Large ABoxes.
Learning Conceptual Space Representations of Interrelated Concepts.
Relevance in Structured Argumentation.
Fast Compliance Checking in an OWL2 Fragment.
Exploiting Justifications for Lazy Grounding of Answer Set Programs.
Actual Causality in a Logical Setting.
Inconsistency-Tolerant Ontology-Based Data Access Revisited: Taking Mappings into Account.
Single-Shot Epistemic Logic Program Solving.
First-Order Rewritability of Frontier-Guarded Ontology-Mediated Queries.
Abstraction of Agents Executing Online and their Abilities in the Situation Calculus.
Compiling Model Representations for Querying Large ABoxes in Expressive DLs.
Explainable Certain Answers.
Enhancing Existential Rules by Closed-World Variables.
Query Answering in Propositional Circumscription.
Personality-Aware Personalized Emotion Recognition from Physiological Signals.
Brain-inspired Balanced Tuning for Spiking Neural Networks.
CSNN: An Augmented Spiking based Framework with Perceptron-Inception.
Memory Attention Networks for Skeleton-based Action Recognition.
Neural Framework for Joint Evolution Modeling of User Feedback and Social Links in Dynamic Social Networks.
Learning Sequential Correlation for User Generated Textual Content Popularity Prediction.
Synthesizing Pattern Programs from Examples.
Cross-Domain Depression Detection via Harvesting Social Media.
A Simple Convolutional Neural Network for Accurate P300 Detection and Character Spelling in Brain Computer Interface.
Jointly Learning Network Connections and Link Weights in Spiking Neural Networks.
Algorithms for Fair Load Shedding in Developing Countries.
NPE: Neural Personalized Embedding for Collaborative Filtering.
Similarity-Based Reasoning, Raven's Matrices, and General Intelligence.
On the Efficiency of Data Collection for Crowdsourced Classification.
A Novel Neural Network Model based on Cerebral Hemispheric Asymmetry for EEG Emotion Recognition.
Simultaneous Clustering and Ranking from Pairwise Comparisons.
Deep Learning Based Multi-modal Addressee Recognition in Visual Scenes with Utterances.
A Novel Strategy for Active Task Assignment in Crowd Labeling.
On the Cost Complexity of Crowdsourcing.
Master-Slave Curriculum Design for Reinforcement Learning.
A Fast Local Search Algorithm for Minimum Weight Dominating Set Problem on Massive Graphs.
Understanding Subgoal Graphs by Augmenting Contraction Hierarchies.
Meta-Level Control of Anytime Algorithms with Online Performance Prediction.
Distributed Pareto Optimization for Subset Selection.
Sequence Selection by Pareto Optimization.
Approximation Guarantees of Stochastic Greedy Algorithms for Subset Selection.
Knowledge-Guided Agent-Tactic-Aware Learning for StarCraft Micromanagement.
Best-Case and Worst-Case Behavior of Greedy Best-First Search.
A Fast Algorithm for Optimally Finding Partially Disjoint Shortest Paths.
An Exact Algorithm for Maximum k-Plexes in Massive Graphs.
Neural Networks for Predicting Algorithm Runtime Distributions.
Anytime Focal Search with Applications.
The FastMap Algorithm for Shortest Path Computations.
Back to Basics: Benchmarking Canonical Evolution Strategies for Playing Atari.
Improving Local Search for Minimum Weight Vertex Cover by Dynamic Strategies.
A General Approach to Running Time Analysis of Multi-objective Evolutionary Algorithms.
A Fast Algorithm for Generalized Arc Consistency of the Alldifferent Constraint.
A Reactive Strategy for High-Level Consistency During Search.
Compact-MDD: Efficiently Filtering (s)MDD Constraints with Reversible Sparse Bit-sets.
Stratification for Constraint-Based Multi-Objective Combinatorial Optimization.
Accelerated Difference of Convex functions Algorithm and its Application to Sparse Binary Logistic Regression.
Learning Optimal Decision Trees with SAT.
Core-Guided Minimal Correction Set and Core Enumeration.
Solving (Weighted) Partial MaxSAT by Dynamic Local Search for SAT.
Solving Exist-Random Quantified Stochastic Boolean Satisfiability via Clause Selection.
DMC: A Distributed Model Counter.
Simpler and Faster Algorithm for Checking the Dynamic Consistency of Conditional Simple Temporal Networks.
Conflict Directed Clause Learning for Maximum Weighted Clique Problem.
Boosting MCSes Enumeration.
Seeking Practical CDCL Insights from Theoretical SAT Benchmarks.
Divide and Conquer: Towards Faster Pseudo-Boolean Solving.
Unary Integer Linear Programming with Structural Restrictions.
Machine Learning and Constraint Programming for Relational-To-Ontology Schema Mapping.
Methods for off-line/on-line optimization under uncertainty.
Descriptive Clustering: ILP and CP Formulations with Applications.
Classification Transfer for Qualitative Reasoning Problems.
On the Satisfiability Threshold of Random Community-Structured SAT.
A Framework for Constraint Based Local Search using Essence.
DehazeGAN: When Image Dehazing Meets Differential Programming.
Centralized Ranking Loss with Weakly Supervised Localization for Fine-Grained Object Retrieval.
Learning Robust Gaussian Process Regression for Visual Tracking.
A Comparative Study of Transactional and Semantic Approaches for Predicting Cascades on Twitter.
A Multi-task Learning Approach for Image Captioning.
Distortion-aware CNNs for Spherical Images.
Hi-Fi: Hierarchical Feature Integration for Skeleton Detection.
3D-Aided Deep Pose-Invariant Face Recognition.
Video Captioning with Tube Features.
Layered Optical Flow Estimation Using a Deep Neural Network with a Soft Mask.
Robust Face Sketch Synthesis via Generative Adversarial Fusion of Priors and Parametric Sigmoid.
High Resolution Feature Recovering for Accelerating Urban Scene Parsing.
Salient Object Detection by Lossless Feature Reflection.
Markov Random Neural Fields for Face Sketch Synthesis.
Better and Faster: Knowledge Transfer from Multiple Self-supervised Learning Tasks via Graph Distillation for Video Classification.
Visual Data Synthesis via GAN for Zero-Shot Video Classification.
SafeNet: Scale-normalization and Anchor-based Feature Extraction Network for Person Re-identification.
Rethinking Diversified and Discriminative Proposal Generation for Visual Grounding.
Exploiting Images for Video Recognition with Hierarchical Generative Adversarial Networks.
Adversarial Attribute-Image Person Re-identification.
Visible Thermal Person Re-Identification via Dual-Constrained Top-Ranking.
Extracting Privileged Information from Untagged Corpora for Classifier Learning.
SSR-Net: A Compact Soft Stagewise Regression Network for Age Estimation.
IncepText: A New Inception-Text Module with Deformable PSROI Pooling for Multi-Oriented Scene Text Detection.
Semantic Structure-based Unsupervised Deep Hashing.
Multi-task Layout Analysis for Historical Handwritten Documents Using Fully Convolutional Networks.
Evaluating Brush Movements for Chinese Calligraphy: A Computer Vision Based Approach.
Fine-grained Image Classification by Visual-Semantic Embedding.
Annotation-Free and One-Shot Learning for Instance Segmentation of Homogeneous Object Clusters.
Multi-modal Circulant Fusion for Video-to-Language and Backward.
Deep Reasoning with Knowledge Graph for Social Relationship Understanding.
HCR-Net: A Hybrid of Classification and Regression Network for Object Pose Estimation.
Densely Cascaded Shadow Detection Network via Deeply Supervised Parallel Fusion.
Deep Propagation Based Image Matting.
Ensemble Soft-Margin Softmax Loss for Image Classification.
Do not Lose the Details: Reinforced Representation Learning for High Performance Visual Tracking.
DRPose3D: Depth Ranking in 3D Human Pose Estimation.
Collaborative Learning for Weakly Supervised Object Detection.
Uncertainty Sampling for Action Recognition via Maximizing Expected Average Precision.
Collaborative and Attentive Learning for Personalized Image Aesthetic Assessment.
Representation Learning for Scene Graph Completion via Jointly Structural and Visual Embedding.
CR-GAN: Learning Complete Representations for Multi-view Generation.
Long-Term Human Motion Prediction by Modeling Motion Context and Enhancing Motion Dynamics.
Image-level to Pixel-wise Labeling: From Theory to Practice.
Learning to Write Stylized Chinese Characters by Reading a Handful of Examples.
Hierarchical Graph Structure Learning for Multi-View 3D Model Retrieval.
From Pixels to Objects: Cubic Visual Attention for Visual Question Answering.
Dual Conditional GANs for Face Aging and Rejuvenation.
Cross-media Multi-level Alignment with Relation Attention Network.
Dilated Convolutional Network with Iterative Optimization for Continuous Sign Language Recognition.
MEGAN: Mixture of Experts of Generative Adversarial Networks for Multimodal Image Generation.
Progressive Generative Hashing for Image Retrieval.
DEL: Deep Embedding Learning for Efficient Image Segmentation.
H-Net: Neural Network for Cross-domain Image Patch Matching.
Crowd Counting using Deep Recurrent Spatial-Aware Network.
When Image Denoising Meets High-Level Vision Tasks: A Deep Learning Approach.
Deep Attribute Guided Representation for Heterogeneous Face Recognition.
Cross-Domain 3D Model Retrieval via Visual Domain Adaption.
Multi-Level Policy and Reward Reinforcement Learning for Image Captioning.
Live Face Verification with Multiple Instantialized Local Homographic Parameterization.
Deeply-Supervised CNN Model for Action Recognition with Trainable Feature Aggregation.
Nonrigid Points Alignment with Soft-weighted Selection.
Image Cationing with Visual-Semantic LSTM.
Co-occurrence Feature Learning from Skeleton Data for Action Recognition and Detection with Hierarchical Aggregation.
Feature Integration with Adaptive Importance Maps for Visual Tracking.
Deep CNN Denoiser and Multi-layer Neighbor Component Embedding for Face Hallucination.
Semantic Locality-Aware Deformable Network for Clothing Segmentation.
Human Motion Generation via Cross-Space Constrained Sampling.
Co-attention CNNs for Unsupervised Object Co-segmentation.
StackDRL: Stacked Deep Reinforcement Learning for Fine-grained Visual Categorization.
Harnessing Synthesized Abstraction Images to Improve Facial Attribute Recognition.
View-Volume Network for Semantic Scene Completion from a Single Depth Image.
Coarse-to-fine Image Co-segmentation with Intra and Inter Rank Constraints.
Age Estimation Using Expectation of Label Distribution Learning.
Watching a Small Portion could be as Good as Watching All: Towards Efficient Video Classification.
Enhanced-alignment Measure for Binary Foreground Map Evaluation.
Unsupervised Cross-Modality Domain Adaptation of ConvNets for Biomedical Image Segmentations with Adversarial Loss.
R³Net: Recurrent Residual Refinement Network for Saliency Detection.
Cross-Modality Person Re-Identification with Generative Adversarial Training.
Siamese CNN-BiLSTM Architecture for 3D Shape Representation Learning.
Dual Adversarial Networks for Zero-shot Cross-media Retrieval.
Anonymizing k Facial Attributes via Adversarial Perturbations.
Multi-scale and Discriminative Part Detectors Based Features for Multi-label Image Classification.
Scanpath Prediction for Visual Attention using IOR-ROI LSTM.
Sharing Residual Units Through Collective Tensor Factorization To Improve Deep Neural Networks.
Knowledge-Embedded Representation Learning for Fine-Grained Image Recognition.
Deep View-Aware Metric Learning for Person Re-Identification.
Learning Deep Unsupervised Binary Codes for Image Retrieval.
Show, Observe and Tell: Attribute-driven Attention Model for Image Captioning.
MEnet: A Metric Expression Network for Salient Object Segmentation.
Strategyproof and Fair Matching Mechanism for Union of Symmetric M-convex Constraints.
Socially Motivated Partial Cooperation in Multi-agent Local Search.
Multiwinner Voting with Restricted Admissible Sets: Complexity and Strategyproofness.
Recurrent Deep Multiagent Q-Learning for Autonomous Brokers in Smart Grid.
Keeping in Touch with Collaborative UAVs: A Deep Reinforcement Learning Approach.
Exact Algorithms and Complexity of Kidney Exchange.
Budget-feasible Procurement Mechanisms in Two-sided Markets.
A Cloaking Mechanism to Mitigate Market Manipulation.
Extended Increasing Cost Tree Search for Non-Unit Cost Domains.
A Decentralised Approach to Intersection Traffic Management.
Efficient Computation of Approximate Equilibria in Discrete Colonel Blotto Games.
Designing the Game to Play: Optimizing Payoff Structure in Security Games.
Ex-post IR Dynamic Auctions with Cost-per-Action Payments.
Redividing the Cake.
Double Auctions in Markets for Multiple Kinds of Goods.
Democratic Fair Allocation of Indivisible Goods.
Deontic Sensors.
Goal-Based Collective Decisions: Axiomatics and Computational Complexity.
Dynamically Forming a Group of Human Forecasters and Machine Forecaster for Forecasting Economic Indicators.
The Price of Usability: Designing Operationalizable Strategies for Security Games.
Leadership in Singleton Congestion Games.
Online Pricing for Revenue Maximization with Unknown Time Discounting Valuations.
Preference Orders on Families of Sets - When Can Impossibility Results Be Avoided?
Optimal Bidding Strategy for Brand Advertising.
Multi-Agent Path Finding with Deadlines.
Maximin Share Allocations on Cycles.
Verifying Emergence of Bounded Time Properties in Probabilistic Swarm Systems.
What Game Are We Playing? End-to-end Learning in Normal and Extensive Form Games.
Equilibrium Behavior in Competing Dynamic Matching Markets.
Integrating Demand Response and Renewable Energy In Wholesale Market.
Dynamic Fair Division Problem with General Valuations.
Customer Sharing in Economic Networks with Costs.
Tractable (Simple) Contests.
Service Exchange Problem.
Combining Opinion Pooling and Evidential Updating for Multi-Agent Consensus.
Approval-Based Multi-Winner Rules and Strategic Voting.
Explaining Multi-Criteria Decision Aiding Models with an Extended Shapley Value.
Symbolic Synthesis of Fault-Tolerance Ratios in Parameterised Multi-Agent Systems.
Computational Social Choice Meets Databases.
Computational Aspects of the Preference Cores of Supermodular Two-Scenario Cooperative Games.
Ceteris paribus majority for social ranking.
Payoff Control in the Iterated Prisoner's Dilemma.
Fostering Cooperation in Structured Populations Through Local and Global Interference Strategies.
Winning a Tournament by Any Means Necessary.
When Rigging a Tournament, Let Greediness Blind You.
Balancing Two-Player Stochastic Games with Soft Q-Learning.
Deep Learning for Multi-Facility Location Mechanism Design.
An Axiomatic View of the Parimutuel Consensus Mechanism.
On Fair Price Discrimination in Multi-Unit Markets.
Probabilistic Verification for Obviously Strategyproof Mechanisms.
Trembling-Hand Perfection in Extensive-Form Games with Commitment.
On the Complexity of Chore Division.
Opinion Diffusion and Campaigning on Society Graphs.
Negotiation Strategies for Agents with Ordinal Preferences.
A Structural Approach to Activity Selection.
An Operational Semantics for a Fragment of PRS.
Facility Reallocation on the Line.
Computing the Schulze Method for Large-Scale Preference Data Sets.
When Does Diversity of Agent Preferences Improve Outcomes in Selfish Routing?
Bidding in Periodic Double Auctions Using Heuristics and Dynamic Monte Carlo Tree Search.
Vocabulary Alignment for Collaborative Agents: a Study with Real-World Multilingual How-to Instructions.
An FPTAS for Computing Nash Equilibrium in Resource Graph Games.
Multiwinner Voting with Fairness Constraints.
Pairwise Liquid Democracy.
Combinatorial Auctions via Machine Learning-based Preference Elicitation.
Solving Patrolling Problems in the Internet Environment.
An Analytical and Experimental Comparison of Maximal Lottery Schemes.
Non-decreasing Payment Rules for Combinatorial Auctions.
Big City vs. the Great Outdoors: Voter Distribution and How It Affects Gerrymandering.
Fair Division Under Cardinality Constraints.
Managing Communication Costs under Temporal Uncertainty.
Alternating-time Temporal Logic on Finite Traces.
Accountable Approval Sorting.
Truthful Fair Division without Free Disposal.
Egalitarian Committee Scoring Rules.
Reasoning about Consensus when Opinions Diffuse through Majority Dynamics.
Comparing Approximate Relaxations of Envy-Freeness.
Synthesis of Controllable Nash Equilibria in Quantitative Objective Game.
Robust Norm Emergence by Revealing and Reasoning about Context: Socially Intelligent Agents for Enhancing Privacy.
Interactive, Collaborative Robots: Challenges and Opportunities.
Model-free, Model-based, and General Intelligence.
Language to Action: Towards Interactive Task Learning with Physical Agents.
