No. 1: Thirty-First AAAI Conference On Artificial Intelligence
Applications
StructInf: Mining Structural Influence from Social Streams
Novel Geometric Approach for Global Alignment of PPI Networks
Towards Better Understanding the Clothing Fashion Styles: A Multimodal Deep Learning Approach
Profit-Driven Team Grouping in Social Networks
Gated Neural Networks for Option Pricing: Rationality by Design
Local Discriminant Hyperalignment for Multi-Subject fMRI Data Alignment
Volumetric ConvNets with Mixed Residual Connections for Automated Prostate Segmentation from 3D MR Images
SnapNETS: Automatic Segmentation of Network Sequences with Node Labels
Taming the Matthew Effect in Online Markets with Social Influence
A Leukocyte Detection Technique in Blood Smear Images Using Plant Growth Simulation Algorithm
Partitioned Sampling of Public Opinions Based on Their Social Dynamics
Artificial Intelligence and the Web
Radon – Rapid Discovery of Topological Relations
Web-Based Semantic Fragment Discovery for On-Line Lingual-Visual Similarity
Exploiting both Vertical and Horizontal Dimensions of Feature Hierarchy for Effective Recommendation
Phrase-Based Presentation Slides Generation for Academic Papers
Community Preserving Network Embedding
CLARE: A Joint Approach to Label Classification and Tag Recommendation
Multiple Source Detection without Knowing the Underlying Propagation Model
Learning Visual Sentiment Distributions via Augmented Conditional Probability Neural Network
Visual Sentiment Analysis by Attending on Local Image Regions
Correlated Cascades: Compete or Cooperate
Finding Critical Users for Social Network Engagement: The Collapsed k-Core Problem
Efficient Delivery Policy to Minimize User Traffic Consumption in Guaranteed Advertising
Expectile Matrix Factorization for Skewed Data Analysis
Transitive Hashing Network for Heterogeneous Multimedia Retrieval
Marrying Uncertainty and Time in Knowledge Graphs
TweetFit: Fusing Multiple Social Media and Sensor Data for Wellness Profile Learning
POI2Vec: Geographical Latent Representation for Predicting Future Visitors
A Dependency-Based Neural Reordering Model for Statistical Machine Translation
Joint Identification of Network Communities and Semantics via Integrative Modeling of Network Topologies and Node Contents
Random-Radius Ball Method for Estimating Closeness Centrality
Read the Silence: Well-Timed Recommendation via Admixture Marked Point Processes
Treatment Effect Estimation with Data-Driven Variable Decomposition
A Declarative Approach to Data-Driven Fact Checking
Semantic Proximity Search on Heterogeneous Graph by Proximity Embedding
Multi-Task Deep Learning for User Intention Understanding in Speech Interaction Systems
Understanding the Semantic Structures of Tables with a Hybrid Deep Neural Network Architecture
Cognitive Modeling and Cognitive Systems
Game Playing and Interactive Entertainment
Game Theory and Economic Paradigms
Randomized Mechanisms for Selling Reserved Instances in Cloud
Sequential Peer Prediction: Learning to Elicit Effort using Posted Prices
An Ambiguity Aversion Model for Decision Making under Ambiguity
Optimal Pricing for Submodular Valuations with Bounded Curvature
On Covering Codes and Upper Bounds for the Dimension of Simple Games
Tractable Algorithms for Approximate Nash Equilibria in Generalized Graphical Games with Tree Structure
Recognising Multidimensional Euclidean Preferences
Preferences Single-Peaked on a Circle
Psychological Forest: Predicting Human Behavior
Revenue Maximization for Finitely Repeated Ad Auctions
Proportional Justified Representation
Achieving Sustainable Cooperation in Generalized Prisoner’s Dilemma with Observation Errors
Mechanism Design for Multi-Type Housing Markets
Constrained Pure Nash Equilibria in Polymatrix Games
Axiomatic Characterization of Game-Theoretic Network Centralities
Social Choice Under Metric Preferences: Scoring Rules and STV
Fans Economy and All-Pay Auctions with Proportional Allocations
The Positronic Economist: A Computational System for Analyzing Economic Mechanisms
Non-Additive Security Games
The Dollar Auction with Spiteful Players
Proper Proxy Scoring Rules
The Computational Complexity of Weighted Greedy Matching
On Markov Games Played by Bayesian and Boundedly-Rational Players
The Complexity of Stable Matchings under Substitutable Preferences
Small Representations of Big Kidney Exchange Graphs
What Do Multiwinner Voting Rules Do? An Experiment Over the Two-Dimensional Euclidean Domain
Extensive-Form Perfect Equilibrium Computation in Two-Player Games
Selfish Knapsack
Obvious Strategyproofness Needs Monitoring for Good Approximations
Crowdsourced Outcome Determination in Prediction Markets
Security Games on a Plane
Engineering Agreement: The Naming Game with Asymmetric and Heterogeneous Agents
Vote Until Two of You Agree: Mechanisms with Small Distortion and Sample Complexity
Computing Least Cores of Supermodular Cooperative Games
Heuristic Search Value Iteration for One-Sided Partially Observable Stochastic Games
Group Activity Selection on Social Networks
Resource Graph Games: A Compact Representation for Games with Structured Strategy Spaces
Complexity of the Stable Invitations Problem
Mechanism Design in Social Networks
Optimal Personalized Defense Strategy Against Man-In-The-Middle Attack
Network, Popularity and Social Cohesion: A Game-Theoretic Approach
Strategic Signaling and Free Information Disclosure in Auctions
Complexity of Manipulating Sequential Allocation
Algorithms for Max-Min Share Fair Allocation of Indivisible Chores
Nash Stability in Social Distance Games
On Pareto Optimality in Social Distance Games
Team-Maxmin Equilibrium: Efficiency Bounds and Algorithms
A Study of Compact Reserve Pricing Languages
Faster and Simpler Algorithm for Optimal Strategies of Blotto Game
Preference Elicitation For Participatory Budgeting
Exclusion Method for Finding Nash Equilibrium in Multiplayer Games
Teams in Online Scheduling Polls: Game-Theoretic Aspects
Probably Approximately Efficient Combinatorial Auctions via Machine Learning
Phragmén’s Voting Methods and Justified Representation
Multiwinner Approval Rules as Apportionment Methods
Dynamic Thresholding and Pruning for Regret Minimization
Optimizing Positional Scoring Rules for Rank Aggregation
Disarmament Games
Bounded Rationality of Restricted Turing Machines
Winner Determination in Huge Elections with MapReduce
Approximation and Parameterized Complexity of Minimax Approval Voting
Market Pricing for Data Streams
Automated Design of Robust Mechanisms
Incentivising Monitoring in Open Normative Systems
Envy-Free Mechanisms with Minimum Number of Cuts
Heuristic Search and Optimization
Non-Monotone DR-Submodular Function Maximization
Regret Ratio Minimization in Multi-Objective Submodular Function Maximization
Value Compression of Pattern Databases
A Fast Algorithm to Compute Maximum k-Plexes in Social Network Analysis
A Unified Convex Surrogate for the Schatten-p Norm
Efficient Stochastic Optimization for Low-Rank Distance Metric Learning
Embedded Bandits for Large-Scale Black-Box Optimization
Reactive Dialectic Search Portfolios for MaxSAT
Efficient Parameter Importance Analysis via Ablation with Surrogates
Problem Difficulty and the Phase Transition in Heuristic Search
Automatic Logic-Based Benders Decomposition with MiniZinc
Parallel Asynchronous Stochastic Variance Reduction for Nonconvex Optimization
A Generic Bet-and-Run Strategy for Speeding Up Stochastic Local Search
The Simultaneous Maze Solving Problem
Going Beyond Primal Treewidth for (M)ILP
Efficient Hyperparameter Optimization for Deep Learning Algorithms Using Deterministic RBF Surrogates
An Exact Algorithm for the Maximum Weight Clique Problem in Large Graphs
Learning to Prune Dominated Action Sequences in Online Black-Box Planning
Systematic Exploration of Larger Local Search Neighborhoods for the Minimum Vertex Cover Problem
New Lower Bound for the Minimum Sum Coloring Problem
Anytime Anyspace AND/OR Search for Bounding the Partition Function
Dancing with Decision Diagrams: A Combined Approach to Exact Cover
Solving High-Dimensional Multi-Objective Optimization Problems with Low Effective Dimensions
Automated Data Extraction Using Predictive Program Synthesis
Grid Pathfinding on the 2k Neighborhoods
Human-Aware Artificial Intelligence
Human Computation and Crowd Sourcing
Humans and Artificial Intelligence
The Benefit in Free Information Disclosure When Selling Information to People
Psychologically Based Virtual-Suspect for Interrogative Interview Training
PIVE: Per-Iteration Visualization Environment for Real-Time Interactions with Dimension Reduction and Clustering
JAG: A Crowdsourcing Framework for Joint Assessment and Peer Grading
On Human Intellect and Machine Failures: Troubleshooting Integrative Machine Learning Systems
Capturing Dependencies among Labels and Features for Multiple Emotion Tagging of Multimedia Data
Knowledge Representation and Reasoning
Don’t Forget the Quantifiable Relationship between Words: Using Recurrent Neural Network for Short Text Topic Discovery
The Symbolic Interior Point Method
Small Is Beautiful: Computing Minimal Equivalent EL Concepts
Compiling Graph Substructures into Sentential Decision Diagrams
Efficient Evaluation of Answer Set Programs with External Sources Based on External Source Inlining
On Equivalence and Inconsistency of Answer Set Programs with External Sources
ProjE: Embedding Projection for Knowledge Graph Completion
Non-Parametric Estimation of Multiple Embeddings for Link Prediction on Dynamic Knowledge Graphs
Causal Discovery Using Regression-Based Conditional Independence Tests
An Improved Algorithm for Learning to Perform Exception-Tolerant Abduction
Trust-Sensitive Evolution of DL-Lite Knowledge Bases
Abstraction in Situation Calculus Action Theories
Source Information Disclosure in Ontology-Based Data Integration
Ontology-Mediated Queries for Probabilistic Databases
Ontology-Based Data Access with a Horn Fragment of Metric Temporal Logic
Solving Advanced Argumentation Problems with Answer-Set Programming
Checking the Consistency of Combined Qualitative Constraint Networks
Add Data into Business Process Verification: Bridging the Gap between Theory and Practice
Practical TBox Abduction Based on Justification Patterns
The Unusual Suspects: Deep Learning Based Mining of Interesting Entity Trivia from Knowledge Graphs
Ontology Materialization by Abstraction Refinement in Horn SHOIF
Number Restrictions on Transitive Roles in Description Logics with Nominals
Strategic Sequences of Arguments for Persuasion Using Decision Trees
Preferential Structures for Comparative Probabilistic Reasoning
Query Answering in DL-Lite with Datatypes: A Non-Uniform Approach
Diagnosability Planning for Controllable Discrete Event Systems
Entropic Causal Inference
SAT Encodings for Distance-Based Belief Merging Operators
LPMLN, Weak Constraints, and P-log
Graph-Based Wrong IsA Relation Detection in a Large-Scale Lexical Taxonomy
On the Transitivity of Hypernym-Hyponym Relations in Data-Driven Lexical Taxonomies
On the Computation of Paracoherent Answer Sets
Polynomially Bounded Logic Programs with Function Symbols: A New Decidable
Machine Learning Applications
Discriminative Semi-Supervised Dictionary Learning with Entropy Regularization for Pattern Classification
Fine-Grained Recurrent Neural Networks for Automatic Prostate Segmentation in Ultrasound Images
Knowledge Transfer for Deep Reinforcement Learning with Hierarchical Experience Replay
Personalized Donor-Recipient Matching for Organ Transplantation
Deep Spatio-Temporal Residual Networks for Citywide Crowd Flows Prediction
Robust Manifold Matrix Factorization for Joint Clustering and Feature Extraction
Discrete Personalized Ranking for Fast Collaborative Filtering from Implicit Feedback
Catch’Em All: Locating Multiple Diffusion Sources in Networks with Partial Observations
Learning Implicit Tasks for Patient-Specific Risk Modeling in ICU
Enabling Dark Energy Science with Deep Generative Models of Galaxy Images
Unsupervised Deep Learning for Optical Flow Estimation
Low-Rank Linear Cold-Start Recommendation from Social Data
Exploring Normalization in Deep Residual Networks with Concatenated Rectified Linear Units
Portfolio Selection via Subset Resampling
Beyond IID: Learning to Combine Non-IID Metrics for Vision Tasks
Fast Inverse Reinforcement Learning with Interval Consistent Graph for Driving Behavior Prediction
Neural Programming by Example
Simultaneous Clustering and Ensemble
A Deep Hierarchical Approach to Lifelong Learning in Minecraft
Learning Attributes from the Crowdsourced Relative Labels
Coupling Implicit and Explicit Knowledge for Customer Volume Prediction
Beyond Monte Carlo Tree Search: Playing Go with Deep Alternative Neural Network and Long-Term Evaluation
Multiset Feature Learning for Highly Imbalanced Data Classification
Adverse Drug Reaction Prediction with Symbolic Latent Dirichlet Allocation
Modeling the Intensity Function of Point Process Via Recurrent Neural Networks
Progressive Prediction of Student Performance in College Programs
Bridging Video Content and Comments: Synchronized Video Description with Temporal Summarization of Crowdsourced Time-Sync Comments
Pairwise Relationship Guided Deep Hashing for Cross-Modal Retrieval
Active Learning with Cross-Class Similarity Transfer
DeepFix: Fixing Common C Language Errors by Deep Learning
Question Difficulty Prediction for READING Problems in Standard Tests
Additional Multi-Touch Attribution for Online Advertising
Multitask Dyadic Prediction and Its Application in Prediction of Adverse Drug-Drug Interaction
Semi-Supervised Multi-View Correlation Feature Learning with Application to Webpage Classification
Contextual RNN-GANs for Abstract Reasoning Diagram Generation
A Framework for Minimal Clustering Modification via Constraint Programming
Knowing What to Ask: A Bayesian Active Learning Approach to the Surveying Problem
ERMMA: Expected Risk Minimization for Matrix Approximation-based Recommender Systems
Learning with Feature Network and Label Network Simultaneously
Collaborative Company Profiling: Insights from an Employee’s Perspective
ESPACE: Accelerating Convolutional Neural Networks via Eliminating Spatial and Channel Redundancy
A Sparse Dictionary Learning Framework to Discover Discriminative Source Activations in EEG Brain Mapping
On Predictive Patent Valuation: Forecasting Patent Citations and Their Types
Let Your Photos Talk: Generating Narrative Paragraph for Photo Stream via Bidirectional Attention Recurrent Neural Networks
Data-Driven Approximations to NP-Hard Problems
Predicting Demographics of High-Resolution Geographies with Geotagged Tweets
Finding Cut from the Same Cloth: Cross Network Link Recommendation via Joint Matrix Factorization
FeaBoost: Joint Feature and Label Refinement for Semantic Segmentation
Explicit Defense Actions Against Test-Set Attacks
Multidimensional Scaling on Multiple Input Distance Matrices
ICU Mortality Prediction: A Classification Algorithm for Imbalanced Datasets
GLOMA: Embedding Global Information in Local Matrix Approximation Models for Collaborative Filtering
Predicting Soccer Highlights from Spatio-Temporal Match Event Streams
A Hybrid Collaborative Filtering Model with Deep Structure for Recommender Systems
Collaborative Dynamic Sparse Topic Regression with User Profile Evolution for Item Recommendation
Event Video Mashup: From Hundreds of Videos to Minutes of Skeleton
Soft Video Parsing by Label Distribution Learning
Machine Learning Methods
Learning Sparse Task Relations in Multi-Task Learning
Multi-View Clustering via Deep Matrix Factorization
SCOPE: Scalable Composite Optimization for Learning on Spark
Lock-Free Optimization for Non-Convex Problems
Scalable Graph Embedding for Asymmetric Proximity
Bilinear Probabilistic Canonical Correlation Analysis via Hybrid Concatenations
Parametric Dual Maximization for Non-Convex Learning Problems
One-Step Spectral Clustering via Dynamically Learning Affinity Matrix and Subspace
Multi-Kernel Low-Rank Dictionary Pair Learning for Multiple Features Based Image Classification
Discover Multiple Novel Labels in Multi-Instance Multi-Label Learning
Improving Efficiency of SVM k-Fold Cross-Validation by Alpha Seeding
Rank Ordering Constraints Elimination with Application for Kernel Learning
Solving Indefinite Kernel Support Vector Machine with Difference of Convex Functions Programming
Cleaning the Null Space: A Privacy Mechanism for Predictors
Efficient Non-Oblivious Randomized Reduction for Risk Minimization with Improved Excess Risk Guarantee
A General Efficient Hyperparameter-Free Algorithm for Convolutional Sparse Learning
Multi-View Correlated Feature Learning by Uncovering Shared Component
A Framework of Online Learning with Imbalanced Streaming Data
TaGiTeD: Predictive Task Guided Tensor Decomposition for Representation Learning from Electronic Health Records
Deep Learning for Fixed Model Reuse
Learning Deep Latent Space for Multi-Label Classification
A Unified Algorithm for One-Cass Structured Matrix Factorization with Side Information
SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient
CBRAP: Contextual Bandits with RAndom Projection
An Exact Penalty Method for Binary Optimization Based on MPEC Formulation
Scalable Feature Selection via Distributed Diversity Maximization
Fast Compressive Phase Retrieval under Bounded Noise
Query-Efficient Imitation Learning for End-to-End Simulated Driving
Growing Interpretable Part Graphs on ConvNets via Multi-Shot Learning
Universum Prescription: Regularization Using Unlabeled Data
How to Train a Compact Binary Neural Network with High Accuracy?
Policy Search with High-Dimensional Context Variables
Coactive Critiquing: Elicitation of Preferences and Features
Importance Sampling with Unequal Support
Achieving Privacy in the Adversarial Multi-Armed Bandit
Thompson Sampling for Stochastic Bandits with Graph Feedback
Selecting Sequences of Items via Submodular Maximization
Variable Kernel Density Estimation in High-Dimensional Feature Spaces
Regularization for Unsupervised Deep Neural Nets
Relational Deep Learning: A Deep Latent Variable Model for Link Prediction
Factorization Bandits for Interactive Recommendation
Latent Smooth Skeleton Embedding
Polynomial Optimization Methods for Matrix Factorization
Two-Dimensional PCA with F-Norm Minimization
Feature Selection Guided Auto-Encoder
Fredholm Multiple Kernel Learning for Semi-Supervised Domain Adaptation
Fast Online Incremental Learning on Mixture Streaming Data
Efficient Ordered Combinatorial Semi-Bandits for Whole-Page Recommendation
Unbiased Multivariate Correlation Analysis
Beyond RPCA: Flattening Complex Noise in the Frequency Domain
Column Networks for Collective Classification
A General Clustering Agreement Index: For Comparing Disjoint and Overlapping Clusters
Non-Negative Inductive Matrix Completion for Discrete Dyadic Data
Online Active Linear Regression via Thresholding
Adaptive Proximal Average Approximation for Composite Convex Minimization
Random Features for Shift-Invariant Kernels with Moment Matching
Compressed K-Means for Large-Scale Clustering
Patch Reordering: A NovelWay to Achieve Rotation and Translation Invariance in Convolutional Neural Networks
Asymmetric Discrete Graph Hashing
Spectral Clustering with Brainstorming Process for Multi-View Data
Parameter Free Large Margin Nearest Neighbor for Distance Metric Learning
Multilinear Regression for Embedded Feature Selection with Application to fMRI Analysis
Distributed Negative Sampling for Word Embeddings
Label-Free Supervision of Neural Networks with Physics and Domain Knowledge
Unsupervised Learning with Truncated Gaussian Graphical Models
Automatic Curriculum Graph Generation for Reinforcement Learning Agents
Self-Correcting Models for Model-Based Reinforcement Learning
Distant Domain Transfer Learning
Confidence-Rated Discriminative Partial Label Learning
Cross-Domain Ranking via Latent Space Learning
When and Why Are Deep Networks Better Than Shallow Ones?
Lifted Inference for Convex Quadratic Programs
Poisson Sum-Product Networks: A Deep Architecture for Tractable Multivariate Poisson Distributions
Deep Collective Inference
Streaming Classification with Emerging New Class by Class Matrix Sketching
Deep Hashing: A Joint Approach for Image Signature Learning
Tsallis Regularized Optimal Transport and Ecological Inference
The Multivariate Generalised von Mises Distribution: Inference and Applications
Querying Partially Labelled Data to Improve a K-nn Classifier
Multi-View Clustering and Semi-Supervised Classification with Adaptive Neighbours
Multiclass Capped ℓp-Norm SVM for Robust Classifications
Unsupervised Large Graph Embedding
Matching Node Embeddings for Graph Similarity
Inductive Pairwise Ranking: Going Beyond the n log(n) Barrier
Active Search in Intensionally Specified Structured Spaces
Top-k Hierarchical Classification
Unimodal Thompson Sampling for Graph-Structured Arms
Accelerated Gradient Temporal Difference Learning
A General Framework for Sparsity Regularized Feature Selection via Iteratively Reweighted Least Square Minimization
Cascade Subspace Clustering
Large Graph Hashing with Spectral Rotation
Low-Rank Tensor Completion with Total Variation for Visual Data Inpainting
Learning Safe Prediction for Semi-Supervised Regression
A Two-Stage Approach for Learning a Sparse Model with Sharp Excess Risk Analysis
Balanced Clustering with Least Square Regression
Ordinal Constrained Binary Code Learning for Nearest Neighbor Search
Sparse Deep Transfer Learning for Convolutional Neural Network
Cost-Sensitive Feature Selection via F-Measure Optimization Reduction
Multiple Kernel k-Means with Incomplete Kernels
Optimal Neighborhood Kernel Clustering with Multiple Kernels
Generalization Analysis for Ranking Using Integral Operator
Infinite Kernel Learning: Generalization Bounds and Algorithms
Accelerated Variance Reduced Stochastic ADMM
Semi-Supervised Classifications via Elastic and Robust Embedding
Approximate Conditional Gradient Descent on Multi-Class Classification
Probabilistic Non-Negative Matrix Factorization and Its Robust Extensions for Topic Modeling
Active Search for Sparse Signals with Region Sensing
Where to Add Actions in Human-in-the-Loop Reinforcement Learning
Asynchronous Stochastic Proximal Optimization Algorithms with Variance Reduction
Generalization Error Bounds for Optimization Algorithms via Stability
Denoising Criterion for Variational Auto-Encoding Framework
Recovering True Classifier Performance in Positive-Unlabeled Learning
Generalized Ambiguity Decompositions for Classification with Applications in Active Learning and Unsupervised Ensemble Pruning
Twin Learning for Similarity and Clustering: A Unified Kernel Approach
Tunable Sensitivity to Large Errors in Neural Network Training
Binary Embedding with Additive Homogeneous Kernels
Structured Inference Networks for Nonlinear State Space Models
Estimating Uncertainty Online Against an Adversary
Learning Non-Linear Dynamics of Decision Boundaries for Maintaining Classification Performance
Identifying Unknown Unknowns in the Open World: Representations and Policies for Guided Exploration
Dynamic Action Repetition for Deep Reinforcement Learning
Playing FPS Games with Deep Reinforcement Learning
Transfer Reinforcement Learning with Shared Dynamics
Transfer Learning for Deep Learning on Graph-Structured Data
Efficient Online Model Adaptation by Incremental Simplex Tableau
Multivariate Hawkes Processes for Large-Scale Inference
Self-Paced Multi-Task Learning
Infinitely Many-Armed Bandits with Budget Constraints
Sparse Subspace Clustering by Learning Approximation ℓ0 Codes
Riemannian Submanifold Tracking on Low-Rank Algebraic Variety
Exploring Commonality and Individuality for Multi-Modal Curriculum Learning
MPGL: An Efficient Matching Pursuit Method for Generalized LASSO
Weighted Bandits or: How Bandits Learn Distorted Values That Are Not Expected
Efficient Sparse Low-Rank Tensor Completion Using the Frank-Wolfe Algorithm
Convex Co-Embedding for Matrix Completion with Predictive Side Information
Continuous Conditional Dependency Network for Structured Regression
Bilateral k-Means Algorithm for Fast Co-Clustering
Alternating Back-Propagation for Generator Network
Enumerate Lasso Solutions for Feature Selection
Scalable Algorithm for Higher-Order Co-Clustering via Random Sampling
Learning Invariant Deep Representation for NIR-VIS Face Recognition
A Generalized Stochastic Variational Bayesian Hyperparameter Learning Framework for Sparse Spectrum Gaussian Process Regression
Semi-Supervised Adaptive Label Distribution Learning for Facial Age Estimation
Sampling Beats Fixed Estimate Predictors for Cloning Stochastic Behavior in Multiagent Systems
Sequential Classification-Based Optimization for Direct Policy Search
A Riemannian Network for SPD Matrix Learning
Asynchronous Mini-Batch Gradient Descent with Variance Reduction for Non-Convex Optimization
Learning Unitary Operators with Help From u(n)
Low-Rank Factorization of Determinantal Point Processes
Robust Loss Functions under Label Noise for Deep Neural Networks
Informative Subspace Learning for Counterfactual Inference
PAC Identification of a Bandit Arm Relative to a Reward Quantile
Classification with Minimax Distance Measures
Latent Discriminant Analysis with Representative Feature Discovery
Near-Optimal Active Learning of Halfspaces via Query Synthesis in the Noisy Setting
Sparse Boltzmann Machines with Structure Learning as Applied to Text Analysis
Communication Lower Bounds for Distributed Convex Optimization: Partition Data on Features
OFFER: Off-Environment Reinforcement Learning
Addressing Imbalance in Multi-Label Classification Using Structured Hellinger Forests
Nonlinear Dynamic Boltzmann Machines for Time-Series Prediction
Estimating the Maximum Expected Value in Continuous Reinforcement Learning Problems
Scalable Multitask Policy Gradient Reinforcement Learning
From Shared Subspaces to Shared Landmarks: A Robust Multi-Source Classification Approach
A Nearly-Black-Box Online Algorithm for Joint Parameter and State Estimation in Temporal Models
Structure Regularized Unsupervised Discriminant Feature Analysis
Self-Paced Learning: An Implicit Regularization Perspective
Deep MIML Network
Modeling Skewed Class Distributions by Reshaping the Concept Space
On Learning High Dimensional Structured Single Index Models
Local Centroids Structured Non-Negative Matrix Factorization
Learning Bayesian Networks with Incomplete Data by Augmentation
Unsupervised Domain Adaptation with a Relaxed Covariate Shift Assumption
Scalable Optimization of Multivariate Performance Measures in Multi-instance Multi-label Learning
The Bernstein Mechanism: Function Release under Differential Privacy
Heavy-Tailed Analogues of the Covariance Matrix for ICA
Fast Generalized Distillation for Semi-Supervised Domain Adaptation
The Option-Critic Architecture
Label Efficient Learning by Exploiting Multi-Class Output Codes
Robust Partially-Compressed Least-Squares
Learning Residual Alternating Automata
Resource Constrained Structured Prediction
Cross-Domain Kernel Induction for Transfer Learning
Multiagent Systems
Improving Surveillance Using Cooperative Target Observation
Query Complexity of Tournament Solutions
Centralized versus Personalized Commitments and Their Influence on Cooperation in Group Interactions
Kont: Computing Tradeoffs in Normative Multiagent Systems
Parameterised Verification of Infinite State Multi-Agent Systems via Predicate Abstraction
Decentralized Planning in Stochastic Environments with Submodular Rewards
Solving Seven Open Problems of Offline and Online Control in Borda Elections
Collective Multiagent Sequential Decision Making Under Uncertainty
Nurturing Group-Beneficial Information-Gathering Behaviors Through Above-Threshold Criteria Setting
Natural Language Processing and Knowledge Representation
Distant Supervision for Relation Extraction with Sentence-Level Attention and Entity Descriptions
Neural Bag-of-Ngrams
SummaRuNNer: A Recurrent Neural Network Based Sequence Model for Extractive Summarization of Documents
Unit Dependency Graph and Its Application to Arithmetic Word Problem Solving
Prerequisite Skills for Reading Comprehension: Multi-Perspective Analysis of MCTest Datasets and Systems
Neural Machine Translation with Reconstruction
SSP: Semantic Space Projection for Knowledge Graph Embedding with Text Descriptions
Efficiently Answering Technical Questions — A Knowledge Graph Approach
Incorporating Knowledge Graph Embeddings into Topic Modeling
A Context-Enriched Neural Network Method for Recognizing Lexical Entailment
Improving Multi-Document Summarization via Text Classification
Natural Language Processing and Machine Learning
Topic Aware Neural Response Generation
Variational Autoencoder for Semi-Supervised Text Classification
Neural Models for Sequence Chunking
BattRAE: Bidimensional Attention-Based Recursive Autoencoders for Learning Bilingual Phrase Embeddings
Bilingual Lexicon Induction from Non-Parallel Data with Minimal Supervision
Active Discriminative Text Representation Learning
Learning Context-Specific Word/Character Embeddings
Mechanism-Aware Neural Machine for Dialogue Response Generation
Disambiguating Spatial Prepositions Using Deep Convolutional Networks
A Unified Model for Cross-Domain and Semi-Supervised Named Entity Recognition in Chinese Social Media
Recurrent Attentional Topic Model
Representations of Context in Recognizing the Figurative and Literal Usages of Idioms
Deterministic Attention for Sequence-to-Sequence Constituent Parsing
S2JSD-LSH: A Locality-Sensitive Hashing Schema for Probability Distributions
Coherent Dialogue with Attention-Based Language Models
Definition Modeling: Learning to Define Word Embeddings in Natural Language
Incrementally Learning the Hierarchical Softmax Function for Neural Language Models
Condensed Memory Networks for Clinical Diagnostic Inferencing
Robsut Wrod Reocginiton via Semi-Character Recurrent Neural Network
Multiresolution Recurrent Neural Networks: An Application to Dialogue Response Generation
A Hierarchical Latent Variable Encoder-Decoder Model for Generating Dialogues
Lattice-Based Recurrent Neural Network Encoders for Neural Machine Translation
Semantic Parsing with Neural Hybrid Trees
Coupled Multi-Layer Attentions for Co-Extraction of Aspect and Opinion Terms
Dual-Clustering Maximum Entropy with Application to Classification and Word Embedding
Neural Machine Translation Advised by Statistical Machine Translation
A Dynamic Window Neural Network for CCG Supertagging
Distinguish Polarity in Bag-of-Words Visualization
Bayesian Neural Word Embedding
Improving Word Embeddings with Convolutional Feature Learning and Subword Information
Joint Copying and Restricted Generation for Paraphrase
Unsupervised Learning of Evolving Relationships Between Literary Characters
Translation Prediction with Source Dependency-Based Context Representation
Maximum Reconstruction Estimation for Generative Latent-Variable Models
Incorporating Expert Knowledge into Keyphrase Extraction
Unsupervised Learning for Lexicon-Based Classification
Open-Vocabulary Semantic Parsing with both Distributional Statistics and Formal Knowledge
Geometry of Compositionality
Natural Language Processing and Text Mining
Salience Estimation via Variational Auto-Encoders for Multi-Document Summarization
Collaborative User Clustering for Short Text Streams
Word Embedding Based Correlation Model for Question/Answer Matching
Greedy Flipping for Constrained Word Deletion
Attentive Interactive Neural Networks for Answer Selection in Community Question Answering
Community-Based Question Answering via Asymmetric Multi-Faceted Ranking Network Learning
Bootstrapping Distantly Supervised IE Using Joint Learning and Small Well-Structured Corpora
Using Discourse Signals for Robust Instructor Intervention Prediction
Automatic Emphatic Information Extraction from Aligned Acoustic Data and Its Application on Sentence Compression
Unsupervised Sentiment Analysis with Signed Social Networks
Recurrent Neural Networks with Auxiliary Labels for Cross-Domain Opinion Target Extraction
Distant Supervision via Prototype-Based Global Representation Learning
What Happens Next? Future Subevent Prediction Using Contextual Hierarchical LSTM
Efficient Dependency-Guided Named Entity Recognition
Improving Event Causality Recognition with Multiple Background Knowledge Sources Using Multi-Column Convolutional Neural Networks
Efficiently Mining High Quality Phrases from Texts
Learning Latent Sentiment Scopes for Entity-Level Sentiment Analysis
Structural Correspondence Learning for Cross-Lingual Sentiment Classification with One-to-Many Mappings
Planning and Scheduling
Schematic Invariants by Reduction to Ground Invariants
Narrowing the Gap Between Saturated and Optimal Cost Partitioning for Classical Planning
Incorporating Domain-Independent Planning Heuristics in Hierarchical Planning
Computational Issues in Time-Inconsistent Planning
Accelerated Vector Pruning for Optimal POMDP Solvers
When to Reset Your Keys: Optimal Timing of Security Updates via Learning
Human-Aware Plan Recognition
Plan Reordering and Parallel Execution — A Parameterized Complexity View
Validating Domains and Plans for Temporal Planning via Encoding into Infinite-State Linear Temporal Logic
On the Disruptive Effectiveness of Automated Planning for LTLf-Based Trace Alignment
Bounding the Probability of Resource Constraint Violations in Multi-Agent MDPs
Optimizing Quantiles in Preference-Based Markov Decision Processes
An Analysis of Monte Carlo Tree Search
An Efficient Approach to Model-Based Hierarchical Reinforcement Learning
Best-First Width Search: Exploration and Exploitation in Classical Planning
Robust Execution of Probabilistic Temporal Plans
Multi-Agent Path Finding with Delay Probabilities
Logical Filtering and Smoothing: State Estimation in Partially Observable Domains
Landmark-Based Heuristics for Goal Recognition
Fast SSP Solvers Using Short-Sighted Labeling
Higher-Dimensional Potential Heuristics for Optimal Classical Planning
Reasoning under Uncertainty
Hindsight Optimization for Hybrid State and Action MDPs
I See What You See: Inferring Sensor and Policy Models of Human Real-World Motor Behavior
Solving Constrained Combinatorial Optimisation Problems via MAP Inference without High-Order Penalties
Anytime Best+Depth-First Search for Bounding Marginal MAP
Multi-Objective Influence Diagrams with Possibly Optimal Policies
Minimal Undefinedness for Fuzzy Answer Sets
Open-Universe Weighted Model Counting
Deterministic versus Probabilistic Methods for Searching for an Evasive Target
Non-Deterministic Planning with Temporally Extended Goals: LTL over Finite and Infinite Traces
Optimizing Expectation with Guarantees in POMDPs
Latent Dependency Forest Models
Causal Effect Identification by Adjustment under Confounding and Selection Biases
The Linearization of Belief Propagation on Pairwise Markov Random Fields
The Kernel Kalman Rule — Efficient Nonparametric Inference with Recursive Least Squares
Misspecified Linear Bandits
Reasoning about Cognitive Trust in Stochastic Multiagent Systems
Robotics
Deep Learning Quadcopter Control via Risk-Aware Active Learning
Latent Dirichlet Allocation for Unsupervised Activity Analysis on an Autonomous Mobile Robot
Unsupervised Feature Learning for 3D Scene Reconstruction with Occupancy Maps
Grounded Action Transformation for Robot Learning in Simulation
A Diversified Generative Latent Variable Model for WiFi-SLAM
Associate Latent Encodings in Learning from Demonstrations
Dynamically Constructed (PO)MDPs for Adaptive Robot Planning
Search and Constraint Satisfaction
RQUERY: Rewriting Natural Language Queries on Knowledge Graphs to Alleviate the Vocabulary Mismatch Problem
CoCoA: A Non-Iterative Approach to a Local Search (A)DCOP Solver
Extending Compact-Table to Negative and Short Tables
General Bounds on Satisfiability Thresholds for Random CSPs via Fourier Analysis
A SAT-Based Approach for Solving the Modal Logic S5-Satisfiability Problem
A BTP-Based Family of Variable Elimination Rules for Binary CSPs
Algorithms for Deciding Counting Quantifiers over Unary Predicates
Maximum Model Counting
Phase Transitions for Scale-Free SAT Formulas
The Opacity of Backbones
Between Subgraph Isomorphism and Maximum Common Subgraph
Should Algorithms for Random SAT and Max-SAT Be Different?
Soft and Cost MDD Propagators
Rigging Nearly Acyclic Tournaments Is Fixed-Parameter Tractable
Vision
Online Multi-Target Tracking Using Recurrent Neural Networks
Text-Guided Attention Model for Image Captioning
Fully Convolutional Neural Networks with Full-Scale-Features for Semantic Segmentation
Title Learning Latent Subevents in Activity Videos Using Temporal Attention Filters
Privacy-Preserving Human Activity Recognition from Extreme Low Resolution
An End-to-End Spatio-Temporal Attention Model for Human Action Recognition from Skeleton Data
Depth CNNs for RGB-D Scene Recognition: Learning from Scratch Better than Transferring from RGB-CNNs
Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning
Image Cosegmentation via Saliency-Guided Constrained Clustering with Cosine Similarity
Quantifying and Detecting Collective Motion by Manifold Learning
Cross-View People Tracking by Scene-Centered Spatio-Temporal Parsing
Unsupervised Learning of Multi-Level Descriptors for Person Re-Identification
Leveraging Saccades to Learn Smooth Pursuit: A Self-Organizing Motion Tracking Model Using Restricted Boltzmann Machines
Efficient Object Instance Search Using Fuzzy Objects Matching
Face Hallucination with Tiny Unaligned Images by Transformative Discriminative Neural Networks
Leveraging Video Descriptions to Learn Video Question Answering
Learning Heterogeneous Dictionary Pair with Feature Projection Matrix for Pedestrian Video Retrieval via Single Query Image
Video Recovery via Learning Variation and Consistency of Images
Nonnegative Orthogonal Graph Matching
Multi-Path Feedback Recurrent Neural Networks for Scene Parsing
Detection and Recognition of Text Embedded in Online Images via Neural Context Models
Weakly Supervised Semantic Segmentation Using Superpixel Pooling Network
Robust MIL-Based Feature Template Learning for Object Tracking
Learning Patch-Based Dynamic Graph for Visual Tracking
Image Caption with Global-Local Attention
Visual Object Tracking for Unmanned Aerial Vehicles: A Benchmark and New Motion Models
A Multiview-Based Parameter Free Framework for Group Detection
Weakly-Supervised Deep Nonnegative Low-Rank Model for Social Image Tag Refinement and Assignment
TextBoxes: A Fast Text Detector with a Single Deep Neural Network
An Artificial Agent for Robust Image Registration
Attention Correctness in Neural Image Captioning
Boosting Complementary Hash Tables for Fast Nearest Neighbor Search
Localizing by Describing: Attribute-Guided Attention Localization for Fine-Grained Recognition
Video Captioning with Listwise Supervision
Closing the Loop for Edge Detection and Object Proposals
Learning Discriminative Activated Simplices for Action Recognition
Non-Rigid Point Set Registration with Robust Transformation Estimation under Manifold Regularization
Regularized Diffusion Process for Visual Retrieval
Collective Deep Quantization for Efficient Cross-Modal Retrieval
Reference Based LSTM for Image Captioning
A Multi-Task Deep Network for Person Re-Identification
VINet: Visual-Inertial Odometry as a Sequence-to-Sequence Learning Problem
Deep Correlated Metric Learning for Sketch-based 3D Shape Retrieval
Deep Manifold Learning of Symmetric Positive Definite Matrices with Application to Face Recognition
Sherlock: Scalable Fact Learning in Images
Robust Visual Tracking via Local-Global Correlation Filter
DECK: Discovering Event Composition Knowledge from Web Images for Zero-Shot Event Detection and Recounting in Videos
Differentiating Between Posed and Spontaneous Expressions with Latent Regression Bayesian Network
Active Video Summarization: Customized Summaries via On-line Interaction with the User
Building an End-to-End Spatial-Temporal Convolutional Network for Video Super-Resolution
Zero-Shot Recognition via Direct Classifier Learning with Transferred Samples and Pseudo Labels
Attributes for Improved Attributes: A Multi-Task Network Utilizing Implicit and Explicit Relationships for Facial Attribute Classification
Weakly Supervised Learning of Part Selection Model with Spatial Constraints for Fine-Grained Image Classification
Special Track on Cognitive Systems
Integrating the Cognitive with the Physical: Musical Path Planning for an Improvising Robot
Imagined Visual Representations as Multimodal Embeddings
Goal Operations for Cognitive Systems
Combining Logical Abduction and Statistical Induction: Discovering Written Primitives with Human Knowledge
Reactive Versus Anticipative Decision Making in a Novel Gift-Giving Game
Towards Continuous Scientific Data Analysis and Hypothesis Evolution
Flexible Model Induction through Heuristic Process Discovery
When Does Bounded-Optimal Metareasoning Favor Few Cognitive Systems?
Scanpath Complexity: Modeling Reading Effort Using Gaze Information
Identifying Useful Inference Paths in Large Commonsense Knowledge Bases by Retrograde Analysis
ConceptNet 5.5: An Open Multilingual Graph of General Knowledge
Towards a Brain Inspired Model of Self-Awareness for Sociable Agents
Semantic Proto-Role Labeling
Natural Language Acquisition and Grounding for Embodied Robotic Systems
Analogical Chaining with Natural Language Instruction for Commonsense Reasoning
Inductive Reasoning about Ontologies Using Conceptual Spaces
Special Track on Computational Sustainability
Species Distribution Modeling of Citizen Science Data as a Classification Problem with Class-Conditional Noise
Combining Satellite Imagery and Open Data to Map Road Safety
Fast-Tracking Stationary MOMDPs for Adaptive Management Problems
Extracting Urban Microclimates from Electricity Bills
Robust Optimization for Tree-Structured Stochastic Network Design
Dynamic Optimization of Landscape Connectivity Embedding Spatial-Capture-Recapture Information
Deep Gaussian Process for Crop Yield Prediction Based on Remote Sensing Data
Matrix Factorisation for Scalable Energy Breakdown
Regularization in Hierarchical Time Series Forecasting with Application to Electricity Smart Meter Data
Maximizing the Probability of Arriving on Time: A Practical Q-Learning Method
Counting-Based Reliability Estimation for Power-Transmission Grids
Three New Algorithms to Solve N-POMDPs
Fine-Grained Car Detection for Visual Census Estimation
Spatial Projection of Multiple Climate Variables Using Hierarchical Multitask Learning
Special Track on Integrated Systems
Healthy Cognitive Aging: A Hybrid Random Vector Functional-Link Model for the Analysis of Alzheimer’s Disease
Mixed Discrete-Continuous Planning with Convex Optimization
Integration of Planning with Recognition for Responsive Interaction Using Classical Planners
Configuration Planning with Temporal Constraints
Learning to Predict Intent from Gaze During Robotic Hand-Eye Coordination
Vision-Language Fusion for Object Recognition
State Projection via AI Planning
Building Task-Oriented Dialogue Systems for Online Shopping
Innovative Applications of Artificial Intelligence Conference: Deployed Application Case Studies
Innovative Applications of Artificial Intelligence Conference: Emerging Application Case Studies
On Designing a Social Coach to Promote Regular Aerobic Exercise
Crowdsensing Air Quality with Camera-Enabled Mobile Devices
Optimal Sequential Drilling for Hydrocarbon Field Development Planning
Predictive Off-Policy Policy Evaluation for Nonstationary Decision Problems, with Applications to Digital Marketing
Using Deep and Convolutional Neural Networks for Accurate Emotion Classification on DEAP Dataset.
A Logic Based Approach to Answering Questions about Alternatives in DIY Domains
ParkUs: A Novel Vehicle Parking Detection System
UbuntuWorld 1.0 LTS — A Platform for Automated Problem Solving & Troubleshooting in the Ubuntu OS
Calories Prediction from Food Images
Real-Time Indoor Localization in Smart Homes Using Semi-Supervised Learning
Constraint-Based Verification of a Mobile App Game Designed for Nudging People to Attend Cancer Screening
Predicting Fuel Consumption and Flight Delays for Low-Cost Airlines
Cracks Under Pressure? Burst Prediction in Water Networks Using Dynamic Metrics
Determining Relative Airport Threats from News and Social Media
Risk-Aware Planning: Methods and Case Study for Safer Driving Routes
Designing Better Playlists with Monte Carlo Tree Search
A Machine Learning Approach for Semantic Structuring of Scientific Charts in Scholarly Documents
Innovative Applications of Artificial Intelligence Conference: Challenge Problem Papers
Educational Advances in Artificial Intelligence Symposium Full Papers
Creating Serious Robots That Improve Society
Recovering Concept Prerequisite Relations from University Course Dependencies
Open-Ended Robotics Exploration Projects for Budding Researchers
Dude, Where’s My Robot?: A Localization Challenge for Undergraduate Robotics
A Monte Carlo Localization Assignment Using a Neato Vacuum with ROS
An Image Wherever You Look! Making Vision Just Another Sensor for AI/Robotics Projects
ARTY: Fueling Creativity through Art, Robotics and Technology for Youth
Cornhole: A Widely-Accessible AI Robotics Task
A Summer Research Experience in Robotics
Educational Advances in Artificial Intelligence Symposium Poster Papers
Educational Advances in Artificial Intelligence Symposium Model AI Assignments
Senior Member Blue Sky
Senior Member Summary Talks
Machine Learning for Entity Coreference Resolution: A Retrospective Look at Two Decades of Research
Incidental Supervision: Moving beyond Supervised Learning
Latent Tree Analysis
A Selected Summary of AI for Computational Sustainability
Explaining Ourselves: Human-Aware Constraint Reasoning
Multi-Robot Allocation of Tasks with Temporal and Ordering Constraints
Progress and Challenges in Research on Cognitive Architectures
Student Abstracts
Attention Based LSTM for Target Dependent Sentiment Classification
Authorship Attribution with Topic Drift Model
Participatory Art Museum: Collecting and Modeling Crowd Opinions
High-Resolution Mobile Fingerprint Matching via Deep Joint KNN-Triplet Embedding
A Computational Assessment Model for the Adaptive Level of Rehabilitation Exergames for the Elderly
Natural Language Person Retrieval
User Modeling Using LSTM Networks
Automatically Extracting Axioms in Classical Planning
SEAPoT-RL: Selective Exploration Algorithm for Policy Transfer in RL
Coalition Structure Generation Utilizing Graphical Representation of Partition Function Games
Audio Feature Learning with Triplet-Based Embedding Network
A Finite Memory Automaton for Two-Armed Bernoulli Bandit Problems
Semantic Representation Using Explicit Concept Space Models
A Sampling Based Approach for Proactive Project Scheduling with Time-Dependent Duration Uncertainty
PAG2ADMG: A Novel Methodology to Enumerate Causal Graph Structures
Preference Elicitation in DCOPs for Scheduling Devices in Smart Buildings
Multimodal Fusion of EEG and Musical Features in Music-Emotion Recognition
Predicting User Roles from Computer Logs Using Recurrent Neural Networks
Extracting Highly Effective Features for Supervised Learning via Simultaneous Tensor Factorization
Hybridizing Interval Temporal Logics: The First Step
Boosting for Real-Time Multivariate Time Series Classification
Semantic Connection Based Topic Evolution
Keyphrase Extraction with Sequential Pattern Mining
Cycle-Based Singleton Local Consistencies
Evolutionary Machine Learning for RTS Game StarCraft
Enhancing the Privacy of Predictors
Detecting Review Spammer Groups
Bootstrapping with Models: Confidence Intervals for Off-Policy Evaluation
Fast Electrical Demand Optimization Under Real-Time Pricing
SReN: Shape Regression Network for Comic Storyboard Extraction
Cross-Domain Sentiment Classification via Topic-Related TrAdaBoost
A Deep Learning Approach for Arabic Caption Generation Using Roots-Words
Learning to Avoid Dominated Action Sequences in Planning for Black-Box Domains
Kernelized Evolutionary Distance Metric Learning for Semi-Supervised Clustering
Redesigning Stochastic Environments for Maximized Utility
Robust and Efficient Transfer Learning with Hidden Parameter Markov Decision Processes
Wikitop: Using Wikipedia Category Network to Generate Topic Trees
Predicting Mortality of Intensive Care Patients via Learning about Hazard
Rethinking the Link Prediction Problem in Signed Social Networks
ATSUM: Extracting Attractive Summaries for News Propagation on Microblogs
A Systematic Practice of Judging the Success of a Robotic Grasp Using Convolutional Neural Network
Neuron Learning Machine for Representation Learning
Community-Based Question Answering via Contextual Ranking Metric Network Learning
Auto-Annotation of 3D Objects via ImageNet
Semantic Interpretation of Social Network Communities
Extreme Gradient Boosting and Behavioral Biometrics
Plan Recognition Design
Improving Performance of Analogue Readout Layers for Photonic Reservoir Computers with Online Learning
Chaotic Time Series Prediction Using a Photonic Reservoir Computer with Output Feedback
Improving Greedy Best-First Search by Removing Unintended Search Bias (Extended Abstract)
Frame-Based Ontology Alignment
Learning Options in Multiobjective Reinforcement Learning
Towards User Personality Profiling from Multiple Social Networks
Semantic Inference of Bird Songs Using Dynamic Bayesian Networks
An Advising Framework for Multiagent Reinforcement Learning Systems
Android Malware Detection with Weak Ground Truth Data
Discovering Conversational Dependencies between Messages in Dialogs
Coordinating Human and Agent Behavior in Collective-Risk Scenarios
The Complexity of Succinct Elections
A Position-Biased PageRank Algorithm for Keyphrase Extraction
Robust Stable Marriage
Handwriting Profiling Using Generative Adversarial Networks
Policy Reuse in Deep Reinforcement Learning
Grounded Action Transformation for Robot Learning in Simulation
Doctoral Consortium
Human-Like Spatial Reasoning Formalisms
Joint Learning of Structural and Textual Features for Web Scale Event Extraction
Scalable Nonparametric Tensor Analysis
Structured Prediction in Time Series Data
A Supervised Sparse Learning Framework to Solve EEG Inverse Problem for Discriminative Activations Pattern
V for Verification: Intelligent Algorithm of Checking Reliability of Smart Systems
Modelling Familiarity for Intelligent Personalized Social Mobilization
Transfer of Knowledge through Collective Learning
Project Scheduling in Complex Business Environments
Explainable Image Understanding Using Vision and Reasoning
Problem Formulation for Accommodation Support in Plan-Based Interactive Narratives
An Evolutionary Algorithm Based Framework for Task Allocation in Multi-Robot Teams
Accelerating Multiagent Reinforcement Learning through Transfer Learning
Improving Deep Reinforcement Learning with Knowledge Transfer
Problems in Large-Scale Image Classification
Representations for Continuous Learning
What's Hot
Demonstrations
SenseRun: Real-Time Running Routes Recommendation towards Providing Pleasant Running Experiences
Natural Language Dialogue for Building and Learning Models and Structures
From Semantic Models to Cognitive Buildings
Deep Music: Towards Musical Dialogue
AniDraw: When Music and Dance Meet Harmoniously
Arnold: An Autonomous Agent to Play FPS Games
A Virtual Personal Fashion Consultant: Learning from the Personal Preference of Fashion
Efficient Clinical Concept Extraction in Electronic Medical Records
Integrating Verbal and Nonvebval Input into a Dynamic Response Spoken Dialogue System
Visual Memory QA: Your Personal Photo and Video Search Agent
Sarcasm Suite: A Browser-Based Engine for Sarcasm Detection and Generation
An Event Reconstruction Tool for Conflict Monitoring Using Social Media
Webly-Supervised Learning of Multimodal Video Detectors