aaai 2017 论文列表Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, February 4-9, 2017, San Francisco, California, USA. |
From Semantic Models to Cognitive Buildings.
Natural Language Dialogue for Building and Learning Models and Structures.
Ian Perera James F. Allen Lucian Galescu Choh Man Teng Mark H. Burstein Scott E. Friedman David D. McDonald Jeffrey M. Rye
SenseRun: Real-Time Running Routes Recommendation towards Providing Pleasant Running Experiences.
Webly-Supervised Learning of Multimodal Video Detectors.
An Event Reconstruction Tool for Conflict Monitoring Using Social Media.
Sarcasm Suite: A Browser-Based Engine for Sarcasm Detection and Generation.
Visual Memory QA: Your Personal Photo and Video Search Agent.
Integrating Verbal and Nonvebval Input into a Dynamic Response Spoken Dialogue System.
Ting-Yao Hu Chirag Raman Salvador Medina Maza Liangke Gui Tadas Baltrusaitis Robert E. Frederking Louis-Philippe Morency Alan W. Black Maxine Eskénazi
Efficient Clinical Concept Extraction in Electronic Medical Records.
A Virtual Personal Fashion Consultant: Learning from the Personal Preference of Fashion.
Arnold: An Autonomous Agent to Play FPS Games.
AniDraw: When Music and Dance Meet Harmoniously.
Deep Music: Towards Musical Dialogue.
The State of the AIIDE Conference in 2017.
What's Hot at CPAIOR (Extended Abstract).
What's Hot in Constraint Programming.
Automated Negotiating Agents Competition (ANAC).
What's Hot in Case-Based Reasoning.
What's Hot in Evolutionary Computation.
SAT Competition 2016: Recent Developments.
Scalable Nonparametric Tensor Analysis.
Joint Learning of Structural and Textual Features for Web Scale Event Extraction.
Human-Like Spatial Reasoning Formalisms.
Project Scheduling in Complex Business Environments.
Transfer of Knowledge through Collective Learning.
Modelling Familiarity for Intelligent Personalized Social Mobilization.
V for Verification: Intelligent Algorithm of Checking Reliability of Smart Systems.
A Supervised Sparse Learning Framework to Solve EEG Inverse Problem for Discriminative Activations Pattern.
Structured Prediction in Time Series Data.
Representations for Continuous Learning.
Problems in Large-Scale Image Classification.
Improving Deep Reinforcement Learning with Knowledge Transfer.
Accelerating Multiagent Reinforcement Learning through Transfer Learning.
An Evolutionary Algorithm Based Framework for Task Allocation in Multi-Robot Teams.
Problem Formulation for Accommodation Support in Plan-Based Interactive Narratives.
Explainable Image Understanding Using Vision and Reasoning.
User Modeling Using LSTM Networks.
Natural Language Person Retrieval.
A Computational Assessment Model for the Adaptive Level of Rehabilitation Exergames for the Elderly.
High-Resolution Mobile Fingerprint Matching via Deep Joint KNN-Triplet Embedding.
Participatory Art Museum: Collecting and Modeling Crowd Opinions.
Authorship Attribution with Topic Drift Model.
Attention Based LSTM for Target Dependent Sentiment Classification.
Detecting Review Spammer Groups.
Enhancing the Privacy of Predictors.
Evolutionary Machine Learning for RTS Game StarCraft.
Cycle-Based Singleton Local Consistencies.
Keyphrase Extraction with Sequential Pattern Mining.
Semantic Connection Based Topic Evolution.
Boosting for Real-Time Multivariate Time Series Classification.
Hybridizing Interval Temporal Logics: The First Step.
Extracting Highly Effective Features for Supervised Learning via Simultaneous Tensor Factorization.
Predicting User Roles from Computer Logs Using Recurrent Neural Networks.
Multimodal Fusion of EEG and Musical Features in Music-Emotion Recognition.
Preference Elicitation in DCOPs for Scheduling Devices in Smart Buildings.
PAG2ADMG: A Novel Methodology to Enumerate Causal Graph Structures.
A Sampling Based Approach for Proactive Project Scheduling with Time-Dependent Duration Uncertainty.
Semantic Representation Using Explicit Concept Space Models.
A Finite Memory Automaton for Two-Armed Bernoulli Bandit Problems.
Audio Feature Learning with Triplet-Based Embedding Network.
Coalition Structure Generation Utilizing Graphical Representation of Partition Function Games.
SEAPoT-RL: Selective Exploration Algorithm for Policy Transfer in RL.
Automatically Extracting Axioms in Classical Planning.
Plan Recognition Design.
Extreme Gradient Boosting and Behavioral Biometrics.
Semantic Interpretation of Social Network Communities.
Auto-Annotation of 3D Objects via ImageNet.
Community-Based Question Answering via Contextual Ranking Metric Network Learning.
Neuron Learning Machine for Representation Learning.
A Systematic Practice of Judging the Success of a Robotic Grasp Using Convolutional Neural Network.
ATSUM: Extracting Attractive Summaries for News Propagation on Microblogs.
Rethinking the Link Prediction Problem in Signed Social Networks.
Predicting Mortality of Intensive Care Patients via Learning about Hazard.
Wikitop: Using Wikipedia Category Network to Generate Topic Trees.
Robust and Efficient Transfer Learning with Hidden Parameter Markov Decision Processes.
Redesigning Stochastic Environments for Maximized Utility.
Kernelized Evolutionary Distance Metric Learning for Semi-Supervised Clustering.
Learning to Avoid Dominated Action Sequences in Planning for Black-Box Domains.
A Deep Learning Approach for Arabic Caption Generation Using Roots-Words.
Cross-Domain Sentiment Classification via Topic-Related TrAdaBoost.
SReN: Shape Regression Network for Comic Storyboard Extraction.
Fast Electrical Demand Optimization Under Real-Time Pricing.
Bootstrapping with Models: Confidence Intervals for Off-Policy Evaluation.
Grounded Action Transformation for Robot Learning in Simulation.
Policy Reuse in Deep Reinforcement Learning.
Handwriting Profiling Using Generative Adversarial Networks.
Robust Stable Marriage.
A Position-Biased PageRank Algorithm for Keyphrase Extraction.
The Complexity of Succinct Elections.
Coordinating Human and Agent Behavior in Collective-Risk Scenarios.
Discovering Conversational Dependencies between Messages in Dialogs.
Android Malware Detection with Weak Ground Truth Data.
An Advising Framework for Multiagent Reinforcement Learning Systems.
Semantic Inference of Bird Songs Using Dynamic Bayesian Networks.
Towards User Personality Profiling from Multiple Social Networks.
Learning Options in Multiobjective Reinforcement Learning.
Frame-Based Ontology Alignment.
Improving Greedy Best-First Search by Removing Unintended Search Bias (Extended Abstract).
Chaotic Time Series Prediction Using a Photonic Reservoir Computer with Output Feedback.
Improving Performance of Analogue Readout Layers for Photonic Reservoir Computers with Online Learning.
Latent Tree Analysis.
Incidental Supervision: Moving beyond Supervised Learning.
Machine Learning for Entity Coreference Resolution: A Retrospective Look at Two Decades of Research.
Progress and Challenges in Research on Cognitive Architectures.
Multi-Robot Allocation of Tasks with Temporal and Ordering Constraints.
Explaining Ourselves: Human-Aware Constraint Reasoning.
A Selected Summary of AI for Computational Sustainability.
Getting More Out of the Exposed Structure in Constraint Programming Models of Combinatorial Problems.
Strategic Social Network Analysis.
Why Teaching Ethics to AI Practitioners Is Important.
Moral Decision Making Frameworks for Artificial Intelligence.
The AI Rebellion: Changing the Narrative.
Model AI Assignments 2017.
Todd W. Neller Joshua Eckroth Sravana Reddy Joshua Ziegler Jason M. Bindewald Gilbert L. Peterson Thomas P. Way Paula Matuszek Lillian N. Cassel Mary-Angela Papalaskari Carol Weiss Ariel Anders Sertac Karaman
AI Projects for Computer Science Capstone Classes (Extended Abstract).
Online SPARC for Drawing and Animation.
Exploring Artificial Intelligence Through Image Recognition.
Application for AI-OCR Module: Auto Detection of Emails/Letter Images.
An Image Wherever You Look! Making Vision Just Another Sensor for AI/Robotics Projects.
A Monte Carlo Localization Assignment Using a Neato Vacuum with ROS.
Dude, Where's My Robot?: A Localization Challenge for Undergraduate Robotics.
Open-Ended Robotics Exploration Projects for Budding Researchers.
Recovering Concept Prerequisite Relations from University Course Dependencies.
Creating Serious Robots That Improve Society.
A Summer Research Experience in Robotics.
Cornhole: A Widely-Accessible AI Robotics Task.
ARTY: Fueling Creativity through Art, Robotics and Technology for Youth.
Explainable Agency for Intelligent Autonomous Systems.
Automated Data Cleansing through Meta-Learning.
A Logic Based Approach to Answering Questions about Alternatives in DIY Domains.
Using Deep and Convolutional Neural Networks for Accurate Emotion Classification on DEAP Dataset.
Predictive Off-Policy Policy Evaluation for Nonstationary Decision Problems, with Applications to Digital Marketing.
Optimal Sequential Drilling for Hydrocarbon Field Development Planning.
Crowdsensing Air Quality with Camera-Enabled Mobile Devices.
On Designing a Social Coach to Promote Regular Aerobic Exercise.
Designing Better Playlists with Monte Carlo Tree Search.
Risk-Aware Planning: Methods and Case Study for Safer Driving Routes.
Determining Relative Airport Threats from News and Social Media.
Rupinder Paul Khandpur Taoran Ji Yue Ning Liang Zhao Chang-Tien Lu Erik R. Smith Christopher Adams Naren Ramakrishnan
Cracks Under Pressure? Burst Prediction in Water Networks Using Dynamic Metrics.
Predicting Fuel Consumption and Flight Delays for Low-Cost Airlines.
Constraint-Based Verification of a Mobile App Game Designed for Nudging People to Attend Cancer Screening.
Real-Time Indoor Localization in Smart Homes Using Semi-Supervised Learning.
Calories Prediction from Food Images.
UbuntuWorld 1.0 LTS - A Platform for Automated Problem Solving & Troubleshooting in the Ubuntu OS.
ParkUs: A Novel Vehicle Parking Detection System.
A Machine Learning Approach for Semantic Structuring of Scientific Charts in Scholarly Documents.
Phase-Mapper: An AI Platform to Accelerate High Throughput Materials Discovery.
Yexiang Xue Junwen Bai Ronan Le Bras Brendan Rappazzo Richard Bernstein Johan Bjorck Liane Longpre Santosh K. Suram Robert Bruce van Dover John M. Gregoire Carla P. Gomes
Large-Scale Occupational Skills Normalization for Online Recruitment.
Building Task-Oriented Dialogue Systems for Online Shopping.
State Projection via AI Planning.
Vision-Language Fusion for Object Recognition.
Learning to Predict Intent from Gaze During Robotic Hand-Eye Coordination.
Configuration Planning with Temporal Constraints.
Integration of Planning with Recognition for Responsive Interaction Using Classical Planners.
Mixed Discrete-Continuous Planning with Convex Optimization.
Healthy Cognitive Aging: A Hybrid Random Vector Functional-Link Model for the Analysis of Alzheimer's Disease.
Deep Gaussian Process for Crop Yield Prediction Based on Remote Sensing Data.
Dynamic Optimization of Landscape Connectivity Embedding Spatial-Capture-Recapture Information.
Robust Optimization for Tree-Structured Stochastic Network Design.
Extracting Urban Microclimates from Electricity Bills.
Fast-Tracking Stationary MOMDPs for Adaptive Management Problems.
Combining Satellite Imagery and Open Data to Map Road Safety.
Species Distribution Modeling of Citizen Science Data as a Classification Problem with Class-Conditional Noise.
Spatial Projection of Multiple Climate Variables Using Hierarchical Multitask Learning.
Fine-Grained Car Detection for Visual Census Estimation.
Three New Algorithms to Solve N-POMDPs.
Counting-Based Reliability Estimation for Power-Transmission Grids.
Maximizing the Probability of Arriving on Time: A Practical Q-Learning Method.
Regularization in Hierarchical Time Series Forecasting with Application to Electricity Smart Meter Data.
Matrix Factorisation for Scalable Energy Breakdown.
Semantic Proto-Role Labeling.
Towards a Brain Inspired Model of Self-Awareness for Sociable Agents.
ConceptNet 5.5: An Open Multilingual Graph of General Knowledge.
Identifying Useful Inference Paths in Large Commonsense Knowledge Bases by Retrograde Analysis.
Scanpath Complexity: Modeling Reading Effort Using Gaze Information.
When Does Bounded-Optimal Metareasoning Favor Few Cognitive Systems?
Flexible Model Induction through Heuristic Process Discovery.
Towards Continuous Scientific Data Analysis and Hypothesis Evolution.
Yolanda Gil Daniel Garijo Varun Ratnakar Rajiv Mayani Ravali Adusumilli Hunter Boyce Arunima Srivastava Parag Mallick
Reactive Versus Anticipative Decision Making in a Novel Gift-Giving Game.
Combining Logical Abduction and Statistical Induction: Discovering Written Primitives with Human Knowledge.
Goal Operations for Cognitive Systems.
Imagined Visual Representations as Multimodal Embeddings.
Integrating the Cognitive with the Physical: Musical Path Planning for an Improvising Robot.
Inductive Reasoning about Ontologies Using Conceptual Spaces.
Analogical Chaining with Natural Language Instruction for Commonsense Reasoning.
Natural Language Acquisition and Grounding for Embodied Robotic Systems.
Learning Heterogeneous Dictionary Pair with Feature Projection Matrix for Pedestrian Video Retrieval via Single Query Image.
Leveraging Video Descriptions to Learn Video Question Answering.
Face Hallucination with Tiny Unaligned Images by Transformative Discriminative Neural Networks.
Efficient Object Instance Search Using Fuzzy Objects Matching.
Leveraging Saccades to Learn Smooth Pursuit: A Self-Organizing Motion Tracking Model Using Restricted Boltzmann Machines.
Unsupervised Learning of Multi-Level Descriptors for Person Re-Identification.
Cross-View People Tracking by Scene-Centered Spatio-Temporal Parsing.
Quantifying and Detecting Collective Motion by Manifold Learning.
Image Cosegmentation via Saliency-Guided Constrained Clustering with Cosine Similarity.
Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning.
Depth CNNs for RGB-D Scene Recognition: Learning from Scratch Better than Transferring from RGB-CNNs.
An End-to-End Spatio-Temporal Attention Model for Human Action Recognition from Skeleton Data.
Privacy-Preserving Human Activity Recognition from Extreme Low Resolution.
Title Learning Latent Subevents in Activity Videos Using Temporal Attention Filters.
Fully Convolutional Neural Networks with Full-Scale-Features for Semantic Segmentation.
Text-Guided Attention Model for Image Captioning.
Online Multi-Target Tracking Using Recurrent Neural Networks.
Non-Rigid Point Set Registration with Robust Transformation Estimation under Manifold Regularization.
Learning Discriminative Activated Simplices for Action Recognition.
Closing the Loop for Edge Detection and Object Proposals.
Video Captioning with Listwise Supervision.
Localizing by Describing: Attribute-Guided Attention Localization for Fine-Grained Recognition.
Boosting Complementary Hash Tables for Fast Nearest Neighbor Search.
Attention Correctness in Neural Image Captioning.
An Artificial Agent for Robust Image Registration.
TextBoxes: A Fast Text Detector with a Single Deep Neural Network.
Weakly-Supervised Deep Nonnegative Low-Rank Model for Social Image Tag Refinement and Assignment.
A Multiview-Based Parameter Free Framework for Group Detection.
Visual Object Tracking for Unmanned Aerial Vehicles: A Benchmark and New Motion Models.
Image Caption with Global-Local Attention.
Learning Patch-Based Dynamic Graph for Visual Tracking.
Robust MIL-Based Feature Template Learning for Object Tracking.
Weakly Supervised Semantic Segmentation Using Superpixel Pooling Network.
Detection and Recognition of Text Embedded in Online Images via Neural Context Models.
Multi-Path Feedback Recurrent Neural Networks for Scene Parsing.
Nonnegative Orthogonal Graph Matching.
Video Recovery via Learning Variation and Consistency of Images.
Weakly Supervised Learning of Part Selection Model with Spatial Constraints for Fine-Grained Image Classification.
Attributes for Improved Attributes: A Multi-Task Network Utilizing Implicit and Explicit Relationships for Facial Attribute Classification.
Zero-Shot Recognition via Direct Classifier Learning with Transferred Samples and Pseudo Labels.
Building an End-to-End Spatial-Temporal Convolutional Network for Video Super-Resolution.
Active Video Summarization: Customized Summaries via On-line Interaction with the User.
Differentiating Between Posed and Spontaneous Expressions with Latent Regression Bayesian Network.
DECK: Discovering Event Composition Knowledge from Web Images for Zero-Shot Event Detection and Recounting in Videos.
Robust Visual Tracking via Local-Global Correlation Filter.
Sherlock: Scalable Fact Learning in Images.
Deep Manifold Learning of Symmetric Positive Definite Matrices with Application to Face Recognition.
Deep Correlated Metric Learning for Sketch-based 3D Shape Retrieval.
VINet: Visual-Inertial Odometry as a Sequence-to-Sequence Learning Problem.
A Multi-Task Deep Network for Person Re-Identification.
Reference Based LSTM for Image Captioning.
Collective Deep Quantization for Efficient Cross-Modal Retrieval.
Regularized Diffusion Process for Visual Retrieval.
General Bounds on Satisfiability Thresholds for Random CSPs via Fourier Analysis.
Extending Compact-Table to Negative and Short Tables.
CoCoA: A Non-Iterative Approach to a Local Search (A)DCOP Solver.
RQUERY: Rewriting Natural Language Queries on Knowledge Graphs to Alleviate the Vocabulary Mismatch Problem.
Rigging Nearly Acyclic Tournaments Is Fixed-Parameter Tractable.
Soft and Cost MDD Propagators.
Should Algorithms for Random SAT and Max-SAT Be Different?
Between Subgraph Isomorphism and Maximum Common Subgraph.
The Opacity of Backbones.
Phase Transitions for Scale-Free SAT Formulas.
Maximum Model Counting.
Algorithms for Deciding Counting Quantifiers over Unary Predicates.
A BTP-Based Family of Variable Elimination Rules for Binary CSPs.
A SAT-Based Approach for Solving the Modal Logic S5-Satisfiability Problem.
Dynamically Constructed (PO)MDPs for Adaptive Robot Planning.
Associate Latent Encodings in Learning from Demonstrations.
A Diversified Generative Latent Variable Model for WiFi-SLAM.
Grounded Action Transformation for Robot Learning in Simulation.
Unsupervised Feature Learning for 3D Scene Reconstruction with Occupancy Maps.
Latent Dirichlet Allocation for Unsupervised Activity Analysis on an Autonomous Mobile Robot.
Deep Learning Quadcopter Control via Risk-Aware Active Learning.
Solving Constrained Combinatorial Optimisation Problems via MAP Inference without High-Order Penalties.
I See What You See: Inferring Sensor and Policy Models of Human Real-World Motor Behavior.
Hindsight Optimization for Hybrid State and Action MDPs.
Multi-Objective Influence Diagrams with Possibly Optimal Policies.
Anytime Best+Depth-First Search for Bounding Marginal MAP.
Reasoning about Cognitive Trust in Stochastic Multiagent Systems.
Misspecified Linear Bandits.
The Kernel Kalman Rule - Efficient Nonparametric Inference with Recursive Least Squares.
The Linearization of Belief Propagation on Pairwise Markov Random Fields.
Causal Effect Identification by Adjustment under Confounding and Selection Biases.
Latent Dependency Forest Models.
Optimizing Expectation with Guarantees in POMDPs.
Non-Deterministic Planning with Temporally Extended Goals: LTL over Finite and Infinite Traces.
Deterministic versus Probabilistic Methods for Searching for an Evasive Target.
Open-Universe Weighted Model Counting.
Minimal Undefinedness for Fuzzy Answer Sets.
Human-Aware Plan Recognition.
When to Reset Your Keys: Optimal Timing of Security Updates via Learning.
Accelerated Vector Pruning for Optimal POMDP Solvers.
Computational Issues in Time-Inconsistent Planning.
Incorporating Domain-Independent Planning Heuristics in Hierarchical Planning.
Narrowing the Gap Between Saturated and Optimal Cost Partitioning for Classical Planning.
Schematic Invariants by Reduction to Ground Invariants.
Higher-Dimensional Potential Heuristics for Optimal Classical Planning.
Fast SSP Solvers Using Short-Sighted Labeling.
Landmark-Based Heuristics for Goal Recognition.
Logical Filtering and Smoothing: State Estimation in Partially Observable Domains.
Multi-Agent Path Finding with Delay Probabilities.
Robust Execution of Probabilistic Temporal Plans.
Best-First Width Search: Exploration and Exploitation in Classical Planning.
An Efficient Approach to Model-Based Hierarchical Reinforcement Learning.
An Analysis of Monte Carlo Tree Search.
Optimizing Quantiles in Preference-Based Markov Decision Processes.
Bounding the Probability of Resource Constraint Violations in Multi-Agent MDPs.
On the Disruptive Effectiveness of Automated Planning for LTLf-Based Trace Alignment.
Validating Domains and Plans for Temporal Planning via Encoding into Infinite-State Linear Temporal Logic.
Plan Reordering and Parallel Execution - A Parameterized Complexity View.
Community-Based Question Answering via Asymmetric Multi-Faceted Ranking Network Learning.
Attentive Interactive Neural Networks for Answer Selection in Community Question Answering.
Greedy Flipping for Constrained Word Deletion.
Word Embedding Based Correlation Model for Question/Answer Matching.
Collaborative User Clustering for Short Text Streams.
Salience Estimation via Variational Auto-Encoders for Multi-Document Summarization.
Structural Correspondence Learning for Cross-Lingual Sentiment Classification with One-to-Many Mappings.
Learning Latent Sentiment Scopes for Entity-Level Sentiment Analysis.
Efficiently Mining High Quality Phrases from Texts.
Improving Event Causality Recognition with Multiple Background Knowledge Sources Using Multi-Column Convolutional Neural Networks.
Efficient Dependency-Guided Named Entity Recognition.
What Happens Next? Future Subevent Prediction Using Contextual Hierarchical LSTM.
Distant Supervision via Prototype-Based Global Representation Learning.
Recurrent Neural Networks with Auxiliary Labels for Cross-Domain Opinion Target Extraction.
Unsupervised Sentiment Analysis with Signed Social Networks.
Automatic Emphatic Information Extraction from Aligned Acoustic Data and Its Application on Sentence Compression.
Using Discourse Signals for Robust Instructor Intervention Prediction.
Bootstrapping Distantly Supervised IE Using Joint Learning and Small Well-Structured Corpora.
Mechanism-Aware Neural Machine for Dialogue Response Generation.
Learning Context-Specific Word/Character Embeddings.
Active Discriminative Text Representation Learning.
Bilingual Lexicon Induction from Non-Parallel Data with Minimal Supervision.
BattRAE: Bidimensional Attention-Based Recursive Autoencoders for Learning Bilingual Phrase Embeddings.
Neural Models for Sequence Chunking.
Variational Autoencoder for Semi-Supervised Text Classification.
Topic Aware Neural Response Generation.
Distinguish Polarity in Bag-of-Words Visualization.
A Dynamic Window Neural Network for CCG Supertagging.
Neural Machine Translation Advised by Statistical Machine Translation.
Dual-Clustering Maximum Entropy with Application to Classification and Word Embedding.
Coupled Multi-Layer Attentions for Co-Extraction of Aspect and Opinion Terms.
Semantic Parsing with Neural Hybrid Trees.
Lattice-Based Recurrent Neural Network Encoders for Neural Machine Translation.
A Hierarchical Latent Variable Encoder-Decoder Model for Generating Dialogues.
Iulian Vlad Serban Alessandro Sordoni Ryan Lowe Laurent Charlin Joelle Pineau Aaron C. Courville Yoshua Bengio
Multiresolution Recurrent Neural Networks: An Application to Dialogue Response Generation.
Iulian Vlad Serban Tim Klinger Gerald Tesauro Kartik Talamadupula Bowen Zhou Yoshua Bengio Aaron C. Courville
Robsut Wrod Reocginiton via Semi-Character Recurrent Neural Network.
Condensed Memory Networks for Clinical Diagnostic Inferencing.
Aaditya Prakash Siyuan Zhao Sadid A. Hasan Vivek V. Datla Kathy Lee Ashequl Qadir Joey Liu Oladimeji Farri
Incrementally Learning the Hierarchical Softmax Function for Neural Language Models.
Definition Modeling: Learning to Define Word Embeddings in Natural Language.
Coherent Dialogue with Attention-Based Language Models.
S2JSD-LSH: A Locality-Sensitive Hashing Schema for Probability Distributions.
Deterministic Attention for Sequence-to-Sequence Constituent Parsing.
Representations of Context in Recognizing the Figurative and Literal Usages of Idioms.
Recurrent Attentional Topic Model.
A Unified Model for Cross-Domain and Semi-Supervised Named Entity Recognition in Chinese Social Media.
Disambiguating Spatial Prepositions Using Deep Convolutional Networks.
Geometry of Compositionality.
Open-Vocabulary Semantic Parsing with both Distributional Statistics and Formal Knowledge.
Unsupervised Learning for Lexicon-Based Classification.
Incorporating Expert Knowledge into Keyphrase Extraction.
Maximum Reconstruction Estimation for Generative Latent-Variable Models.
Translation Prediction with Source Dependency-Based Context Representation.
Unsupervised Learning of Evolving Relationships Between Literary Characters.
Joint Copying and Restricted Generation for Paraphrase.
Improving Word Embeddings with Convolutional Feature Learning and Subword Information.
Bayesian Neural Word Embedding.
A Context-Enriched Neural Network Method for Recognizing Lexical Entailment.
Incorporating Knowledge Graph Embeddings into Topic Modeling.
Efficiently Answering Technical Questions - A Knowledge Graph Approach.
SSP: Semantic Space Projection for Knowledge Graph Embedding with Text Descriptions.
Neural Machine Translation with Reconstruction.
Prerequisite Skills for Reading Comprehension: Multi-Perspective Analysis of MCTest Datasets and Systems.
Unit Dependency Graph and Its Application to Arithmetic Word Problem Solving.
SummaRuNNer: A Recurrent Neural Network Based Sequence Model for Extractive Summarization of Documents.
Neural Bag-of-Ngrams.
Distant Supervision for Relation Extraction with Sentence-Level Attention and Entity Descriptions.
Improving Multi-Document Summarization via Text Classification.
Nurturing Group-Beneficial Information-Gathering Behaviors Through Above-Threshold Criteria Setting.
Collective Multiagent Sequential Decision Making Under Uncertainty.
Solving Seven Open Problems of Offline and Online Control in Borda Elections.
Decentralized Planning in Stochastic Environments with Submodular Rewards.
Parameterised Verification of Infinite State Multi-Agent Systems via Predicate Abstraction.
Kont: Computing Tradeoffs in Normative Multiagent Systems.
Centralized versus Personalized Commitments and Their Influence on Cooperation in Group Interactions.
Query Complexity of Tournament Solutions.
Improving Surveillance Using Cooperative Target Observation.
Discover Multiple Novel Labels in Multi-Instance Multi-Label Learning.
Multi-Kernel Low-Rank Dictionary Pair Learning for Multiple Features Based Image Classification.
One-Step Spectral Clustering via Dynamically Learning Affinity Matrix and Subspace.
Parametric Dual Maximization for Non-Convex Learning Problems.
Bilinear Probabilistic Canonical Correlation Analysis via Hybrid Concatenations.
Scalable Graph Embedding for Asymmetric Proximity.
Lock-Free Optimization for Non-Convex Problems.
SCOPE: Scalable Composite Optimization for Learning on Spark.
Multi-View Clustering via Deep Matrix Factorization.
Learning Sparse Task Relations in Multi-Task Learning.
Universum Prescription: Regularization Using Unlabeled Data.
Growing Interpretable Part Graphs on ConvNets via Multi-Shot Learning.
Query-Efficient Imitation Learning for End-to-End Simulated Driving.
Fast Compressive Phase Retrieval under Bounded Noise.
Scalable Feature Selection via Distributed Diversity Maximization.
An Exact Penalty Method for Binary Optimization Based on MPEC Formulation.
CBRAP: Contextual Bandits with RAndom Projection.
SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient.
A Unified Algorithm for One-Cass Structured Matrix Factorization with Side Information.
Learning Deep Latent Space for Multi-Label Classification.
Deep Learning for Fixed Model Reuse.
TaGiTeD: Predictive Task Guided Tensor Decomposition for Representation Learning from Electronic Health Records.
A Framework of Online Learning with Imbalanced Streaming Data.
Multi-View Correlated Feature Learning by Uncovering Shared Component.
A General Efficient Hyperparameter-Free Algorithm for Convolutional Sparse Learning.
Efficient Non-Oblivious Randomized Reduction for Risk Minimization with Improved Excess Risk Guarantee.
Cleaning the Null Space: A Privacy Mechanism for Predictors.
Solving Indefinite Kernel Support Vector Machine with Difference of Convex Functions Programming.
Rank Ordering Constraints Elimination with Application for Kernel Learning.
Improving Efficiency of SVM k-Fold Cross-Validation by Alpha Seeding.
Beyond RPCA: Flattening Complex Noise in the Frequency Domain.
Unbiased Multivariate Correlation Analysis.
Efficient Ordered Combinatorial Semi-Bandits for Whole-Page Recommendation.
Fast Online Incremental Learning on Mixture Streaming Data.
Fredholm Multiple Kernel Learning for Semi-Supervised Domain Adaptation.
Feature Selection Guided Auto-Encoder.
Two-Dimensional PCA with F-Norm Minimization.
Polynomial Optimization Methods for Matrix Factorization.
Latent Smooth Skeleton Embedding.
Factorization Bandits for Interactive Recommendation.
Relational Deep Learning: A Deep Latent Variable Model for Link Prediction.
Regularization for Unsupervised Deep Neural Nets.
Variable Kernel Density Estimation in High-Dimensional Feature Spaces.
Selecting Sequences of Items via Submodular Maximization.
Thompson Sampling for Stochastic Bandits with Graph Feedback.
Achieving Privacy in the Adversarial Multi-Armed Bandit.
Importance Sampling with Unequal Support.
Coactive Critiquing: Elicitation of Preferences and Features.
Policy Search with High-Dimensional Context Variables.
How to Train a Compact Binary Neural Network with High Accuracy?
Cross-Domain Ranking via Latent Space Learning.
Confidence-Rated Discriminative Partial Label Learning.
Distant Domain Transfer Learning.
Self-Correcting Models for Model-Based Reinforcement Learning.
Automatic Curriculum Graph Generation for Reinforcement Learning Agents.
Unsupervised Learning with Truncated Gaussian Graphical Models.
Label-Free Supervision of Neural Networks with Physics and Domain Knowledge.
Distributed Negative Sampling for Word Embeddings.
Multilinear Regression for Embedded Feature Selection with Application to fMRI Analysis.
Parameter Free Large Margin Nearest Neighbor for Distance Metric Learning.
Spectral Clustering with Brainstorming Process for Multi-View Data.
Asymmetric Discrete Graph Hashing.
Patch Reordering: A NovelWay to Achieve Rotation and Translation Invariance in Convolutional Neural Networks.
Compressed K-Means for Large-Scale Clustering.
Random Features for Shift-Invariant Kernels with Moment Matching.
Adaptive Proximal Average Approximation for Composite Convex Minimization.
Online Active Linear Regression via Thresholding.
Non-Negative Inductive Matrix Completion for Discrete Dyadic Data.
A General Clustering Agreement Index: For Comparing Disjoint and Overlapping Clusters.
Column Networks for Collective Classification.
Cascade Subspace Clustering.
A General Framework for Sparsity Regularized Feature Selection via Iteratively Reweighted Least Square Minimization.
Accelerated Gradient Temporal Difference Learning.
Unimodal Thompson Sampling for Graph-Structured Arms.
Top-k Hierarchical Classification.
Active Search in Intensionally Specified Structured Spaces.
Inductive Pairwise Ranking: Going Beyond the n log(n) Barrier.
Matching Node Embeddings for Graph Similarity.
Unsupervised Large Graph Embedding.
Multiclass Capped ℓp-Norm SVM for Robust Classifications.
Multi-View Clustering and Semi-Supervised Classification with Adaptive Neighbours.
Querying Partially Labelled Data to Improve a K-nn Classifier.
The Multivariate Generalised von Mises Distribution: Inference and Applications.
Tsallis Regularized Optimal Transport and Ecological Inference.
Deep Hashing: A Joint Approach for Image Signature Learning.
Streaming Classification with Emerging New Class by Class Matrix Sketching.
Deep Collective Inference.
Poisson Sum-Product Networks: A Deep Architecture for Tractable Multivariate Poisson Distributions.
Lifted Inference for Convex Quadratic Programs.
When and Why Are Deep Networks Better Than Shallow Ones?
Generalization Error Bounds for Optimization Algorithms via Stability.
Asynchronous Stochastic Proximal Optimization Algorithms with Variance Reduction.
Where to Add Actions in Human-in-the-Loop Reinforcement Learning.
Active Search for Sparse Signals with Region Sensing.
Probabilistic Non-Negative Matrix Factorization and Its Robust Extensions for Topic Modeling.
Approximate Conditional Gradient Descent on Multi-Class Classification.
Semi-Supervised Classifications via Elastic and Robust Embedding.
Accelerated Variance Reduced Stochastic ADMM.
Infinite Kernel Learning: Generalization Bounds and Algorithms.
Generalization Analysis for Ranking Using Integral Operator.
Optimal Neighborhood Kernel Clustering with Multiple Kernels.
Multiple Kernel k-Means with Incomplete Kernels.
Cost-Sensitive Feature Selection via F-Measure Optimization Reduction.
Sparse Deep Transfer Learning for Convolutional Neural Network.
Ordinal Constrained Binary Code Learning for Nearest Neighbor Search.
Balanced Clustering with Least Square Regression.
A Two-Stage Approach for Learning a Sparse Model with Sharp Excess Risk Analysis.
Learning Safe Prediction for Semi-Supervised Regression.
Low-Rank Tensor Completion with Total Variation for Visual Data Inpainting.
Large Graph Hashing with Spectral Rotation.
Riemannian Submanifold Tracking on Low-Rank Algebraic Variety.
Sparse Subspace Clustering by Learning Approximation ℓ0 Codes.
Infinitely Many-Armed Bandits with Budget Constraints.
Self-Paced Multi-Task Learning.
Multivariate Hawkes Processes for Large-Scale Inference.
Efficient Online Model Adaptation by Incremental Simplex Tableau.
Transfer Learning for Deep Learning on Graph-Structured Data.
Transfer Reinforcement Learning with Shared Dynamics.
Playing FPS Games with Deep Reinforcement Learning.
Dynamic Action Repetition for Deep Reinforcement Learning.
Identifying Unknown Unknowns in the Open World: Representations and Policies for Guided Exploration.
Learning Non-Linear Dynamics of Decision Boundaries for Maintaining Classification Performance.
Estimating Uncertainty Online Against an Adversary.
Structured Inference Networks for Nonlinear State Space Models.
Binary Embedding with Additive Homogeneous Kernels.
Tunable Sensitivity to Large Errors in Neural Network Training.
Twin Learning for Similarity and Clustering: A Unified Kernel Approach.
Generalized Ambiguity Decompositions for Classification with Applications in Active Learning and Unsupervised Ensemble Pruning.
Recovering True Classifier Performance in Positive-Unlabeled Learning.
Denoising Criterion for Variational Auto-Encoding Framework.
Learning Unitary Operators with Help From u(n).
Asynchronous Mini-Batch Gradient Descent with Variance Reduction for Non-Convex Optimization.
A Riemannian Network for SPD Matrix Learning.
Sequential Classification-Based Optimization for Direct Policy Search.
Sampling Beats Fixed Estimate Predictors for Cloning Stochastic Behavior in Multiagent Systems.
Semi-Supervised Adaptive Label Distribution Learning for Facial Age Estimation.
A Generalized Stochastic Variational Bayesian Hyperparameter Learning Framework for Sparse Spectrum Gaussian Process Regression.
Learning Invariant Deep Representation for NIR-VIS Face Recognition.
Scalable Algorithm for Higher-Order Co-Clustering via Random Sampling.
Enumerate Lasso Solutions for Feature Selection.
Alternating Back-Propagation for Generator Network.
Bilateral k-Means Algorithm for Fast Co-Clustering.
Continuous Conditional Dependency Network for Structured Regression.
Convex Co-Embedding for Matrix Completion with Predictive Side Information.
Efficient Sparse Low-Rank Tensor Completion Using the Frank-Wolfe Algorithm.
Weighted Bandits or: How Bandits Learn Distorted Values That Are Not Expected.
MPGL: An Efficient Matching Pursuit Method for Generalized LASSO.
Exploring Commonality and Individuality for Multi-Modal Curriculum Learning.
Robust Loss Functions under Label Noise for Deep Neural Networks.
Low-Rank Factorization of Determinantal Point Processes.
Local Centroids Structured Non-Negative Matrix Factorization.
On Learning High Dimensional Structured Single Index Models.
Modeling Skewed Class Distributions by Reshaping the Concept Space.
Deep MIML Network.
Self-Paced Learning: An Implicit Regularization Perspective.
Structure Regularized Unsupervised Discriminant Feature Analysis.
A Nearly-Black-Box Online Algorithm for Joint Parameter and State Estimation in Temporal Models.
From Shared Subspaces to Shared Landmarks: A Robust Multi-Source Classification Approach.
Sarah M. Erfani Mahsa Baktashmotlagh Masud Moshtaghi Vinh Nguyen Christopher Leckie James Bailey Kotagiri Ramamohanarao
Scalable Multitask Policy Gradient Reinforcement Learning.
Estimating the Maximum Expected Value in Continuous Reinforcement Learning Problems.
Nonlinear Dynamic Boltzmann Machines for Time-Series Prediction.
Addressing Imbalance in Multi-Label Classification Using Structured Hellinger Forests.
OFFER: Off-Environment Reinforcement Learning.
Communication Lower Bounds for Distributed Convex Optimization: Partition Data on Features.
Sparse Boltzmann Machines with Structure Learning as Applied to Text Analysis.
Near-Optimal Active Learning of Halfspaces via Query Synthesis in the Noisy Setting.
Latent Discriminant Analysis with Representative Feature Discovery.
Classification with Minimax Distance Measures.
PAC Identification of a Bandit Arm Relative to a Reward Quantile.
Informative Subspace Learning for Counterfactual Inference.
Cross-Domain Kernel Induction for Transfer Learning.
Resource Constrained Structured Prediction.
Learning Residual Alternating Automata.
Robust Partially-Compressed Least-Squares.
Label Efficient Learning by Exploiting Multi-Class Output Codes.
The Option-Critic Architecture.
Fast Generalized Distillation for Semi-Supervised Domain Adaptation.
Heavy-Tailed Analogues of the Covariance Matrix for ICA.
The Bernstein Mechanism: Function Release under Differential Privacy.
Scalable Optimization of Multivariate Performance Measures in Multi-instance Multi-label Learning.
Apoorv Aggarwal Sandip Ghoshal Ankith M. S. Shetty Suhit Sinha Ganesh Ramakrishnan Purushottam Kar Prateek Jain
Unsupervised Domain Adaptation with a Relaxed Covariate Shift Assumption.
Learning Bayesian Networks with Incomplete Data by Augmentation.
Catch'Em All: Locating Multiple Diffusion Sources in Networks with Partial Observations.
Discrete Personalized Ranking for Fast Collaborative Filtering from Implicit Feedback.
Robust Manifold Matrix Factorization for Joint Clustering and Feature Extraction.
Deep Spatio-Temporal Residual Networks for Citywide Crowd Flows Prediction.
Personalized Donor-Recipient Matching for Organ Transplantation.
Knowledge Transfer for Deep Reinforcement Learning with Hierarchical Experience Replay.
Fine-Grained Recurrent Neural Networks for Automatic Prostate Segmentation in Ultrasound Images.
Discriminative Semi-Supervised Dictionary Learning with Entropy Regularization for Pattern Classification.
Pairwise Relationship Guided Deep Hashing for Cross-Modal Retrieval.
Bridging Video Content and Comments: Synchronized Video Description with Temporal Summarization of Crowdsourced Time-Sync Comments.
Progressive Prediction of Student Performance in College Programs.
Modeling the Intensity Function of Point Process Via Recurrent Neural Networks.
Adverse Drug Reaction Prediction with Symbolic Latent Dirichlet Allocation.
Multiset Feature Learning for Highly Imbalanced Data Classification.
Beyond Monte Carlo Tree Search: Playing Go with Deep Alternative Neural Network and Long-Term Evaluation.
Coupling Implicit and Explicit Knowledge for Customer Volume Prediction.
Learning Attributes from the Crowdsourced Relative Labels.
A Deep Hierarchical Approach to Lifelong Learning in Minecraft.
Simultaneous Clustering and Ensemble.
Neural Programming by Example.
Fast Inverse Reinforcement Learning with Interval Consistent Graph for Driving Behavior Prediction.
Beyond IID: Learning to Combine Non-IID Metrics for Vision Tasks.
Portfolio Selection via Subset Resampling.
Exploring Normalization in Deep Residual Networks with Concatenated Rectified Linear Units.
Low-Rank Linear Cold-Start Recommendation from Social Data.
Unsupervised Deep Learning for Optical Flow Estimation.
Enabling Dark Energy Science with Deep Generative Models of Galaxy Images.
Learning Implicit Tasks for Patient-Specific Risk Modeling in ICU.
FeaBoost: Joint Feature and Label Refinement for Semantic Segmentation.
Finding Cut from the Same Cloth: Cross Network Link Recommendation via Joint Matrix Factorization.
Predicting Demographics of High-Resolution Geographies with Geotagged Tweets.
Data-Driven Approximations to NP-Hard Problems.
Let Your Photos Talk: Generating Narrative Paragraph for Photo Stream via Bidirectional Attention Recurrent Neural Networks.
On Predictive Patent Valuation: Forecasting Patent Citations and Their Types.
A Sparse Dictionary Learning Framework to Discover Discriminative Source Activations in EEG Brain Mapping.
ESPACE: Accelerating Convolutional Neural Networks via Eliminating Spatial and Channel Redundancy.
Collaborative Company Profiling: Insights from an Employee's Perspective.
Learning with Feature Network and Label Network Simultaneously.
ERMMA: Expected Risk Minimization for Matrix Approximation-based Recommender Systems.
Knowing What to Ask: A Bayesian Active Learning Approach to the Surveying Problem.
A Framework for Minimal Clustering Modification via Constraint Programming.
Contextual RNN-GANs for Abstract Reasoning Diagram Generation.
Semi-Supervised Multi-View Correlation Feature Learning with Application to Webpage Classification.
Multitask Dyadic Prediction and Its Application in Prediction of Adverse Drug-Drug Interaction.
Additional Multi-Touch Attribution for Online Advertising.
Question Difficulty Prediction for READING Problems in Standard Tests.
DeepFix: Fixing Common C Language Errors by Deep Learning.
Active Learning with Cross-Class Similarity Transfer.
Soft Video Parsing by Label Distribution Learning.
Event Video Mashup: From Hundreds of Videos to Minutes of Skeleton.
Collaborative Dynamic Sparse Topic Regression with User Profile Evolution for Item Recommendation.
A Hybrid Collaborative Filtering Model with Deep Structure for Recommender Systems.
Predicting Soccer Highlights from Spatio-Temporal Match Event Streams.
GLOMA: Embedding Global Information in Local Matrix Approximation Models for Collaborative Filtering.
ICU Mortality Prediction: A Classification Algorithm for Imbalanced Datasets.
Multidimensional Scaling on Multiple Input Distance Matrices.
Explicit Defense Actions Against Test-Set Attacks.
Trust-Sensitive Evolution of DL-Lite Knowledge Bases.
An Improved Algorithm for Learning to Perform Exception-Tolerant Abduction.
Causal Discovery Using Regression-Based Conditional Independence Tests.
Non-Parametric Estimation of Multiple Embeddings for Link Prediction on Dynamic Knowledge Graphs.
ProjE: Embedding Projection for Knowledge Graph Completion.
On Equivalence and Inconsistency of Answer Set Programs with External Sources.
Efficient Evaluation of Answer Set Programs with External Sources Based on External Source Inlining.
Compiling Graph Substructures into Sentential Decision Diagrams.
Small Is Beautiful: Computing Minimal Equivalent EL Concepts.
The Symbolic Interior Point Method.
Don't Forget the Quantifiable Relationship between Words: Using Recurrent Neural Network for Short Text Topic Discovery.
On the Transitivity of Hypernym-Hyponym Relations in Data-Driven Lexical Taxonomies.
Graph-Based Wrong IsA Relation Detection in a Large-Scale Lexical Taxonomy.
LPMLN, Weak Constraints, and P-log.
SAT Encodings for Distance-Based Belief Merging Operators.
Entropic Causal Inference.
Diagnosability Planning for Controllable Discrete Event Systems.
Query Answering in DL-Lite with Datatypes: A Non-Uniform Approach.
Preferential Structures for Comparative Probabilistic Reasoning.
Strategic Sequences of Arguments for Persuasion Using Decision Trees.
Number Restrictions on Transitive Roles in Description Logics with Nominals.
Ontology Materialization by Abstraction Refinement in Horn SHOIF.
The Unusual Suspects: Deep Learning Based Mining of Interesting Entity Trivia from Knowledge Graphs.
Practical TBox Abduction Based on Justification Patterns.
Add Data into Business Process Verification: Bridging the Gap between Theory and Practice.
Checking the Consistency of Combined Qualitative Constraint Networks.
Solving Advanced Argumentation Problems with Answer-Set Programming.
Ontology-Based Data Access with a Horn Fragment of Metric Temporal Logic.
Sebastian Brandt Elem Güzel Kalayci Roman Kontchakov Vladislav Ryzhikov Guohui Xiao Michael Zakharyaschev
Ontology-Mediated Queries for Probabilistic Databases.
Source Information Disclosure in Ontology-Based Data Integration.
Abstraction in Situation Calculus Action Theories.
Polynomially Bounded Logic Programs with Function Symbols: A New Decidable.
On the Computation of Paracoherent Answer Sets.
Capturing Dependencies among Labels and Features for Multiple Emotion Tagging of Multimedia Data.
On Human Intellect and Machine Failures: Troubleshooting Integrative Machine Learning Systems.
JAG: A Crowdsourcing Framework for Joint Assessment and Peer Grading.
PIVE: Per-Iteration Visualization Environment for Real-Time Interactions with Dimension Reduction and Clustering.
Psychologically Based Virtual-Suspect for Interrogative Interview Training.
The Benefit in Free Information Disclosure When Selling Information to People.
Pairwise HITS: Quality Estimation from Pairwise Comparisons in Creator-Evaluator Crowdsourcing Process.
A Theoretical Analysis of First Heuristics of Crowdsourced Entity Resolution.
Long-Term Trends in the Public Perception of Artificial Intelligence.
Collaborative Planning with Encoding of Users' High-Level Strategies.
Predicting Latent Narrative Mood Using Audio and Physiologic Data.
Examples-Rules Guided Deep Neural Network for Makeup Recommendation.
Efficient Stochastic Optimization for Low-Rank Distance Metric Learning.
A Unified Convex Surrogate for the Schatten-p Norm.
A Fast Algorithm to Compute Maximum k-Plexes in Social Network Analysis.
Value Compression of Pattern Databases.
Regret Ratio Minimization in Multi-Objective Submodular Function Maximization.
Non-Monotone DR-Submodular Function Maximization.
Grid Pathfinding on the 2k Neighborhoods.
Automated Data Extraction Using Predictive Program Synthesis.
Solving High-Dimensional Multi-Objective Optimization Problems with Low Effective Dimensions.
Dancing with Decision Diagrams: A Combined Approach to Exact Cover.
Anytime Anyspace AND/OR Search for Bounding the Partition Function.
New Lower Bound for the Minimum Sum Coloring Problem.
Systematic Exploration of Larger Local Search Neighborhoods for the Minimum Vertex Cover Problem.
Learning to Prune Dominated Action Sequences in Online Black-Box Planning.
An Exact Algorithm for the Maximum Weight Clique Problem in Large Graphs.
Efficient Hyperparameter Optimization for Deep Learning Algorithms Using Deterministic RBF Surrogates.
Going Beyond Primal Treewidth for (M)ILP.
The Simultaneous Maze Solving Problem.
A Generic Bet-and-Run Strategy for Speeding Up Stochastic Local Search.
Parallel Asynchronous Stochastic Variance Reduction for Nonconvex Optimization.
Automatic Logic-Based Benders Decomposition with MiniZinc.
Problem Difficulty and the Phase Transition in Heuristic Search.
Efficient Parameter Importance Analysis via Ablation with Surrogates.
Reactive Dialectic Search Portfolios for MaxSAT.
Embedded Bandits for Large-Scale Black-Box Optimization.
Randomized Mechanisms for Selling Reserved Instances in Cloud Computing.
Proper Proxy Scoring Rules.
The Dollar Auction with Spiteful Players.
Non-Additive Security Games.
The Positronic Economist: A Computational System for Analyzing Economic Mechanisms.
Fans Economy and All-Pay Auctions with Proportional Allocations.
Social Choice Under Metric Preferences: Scoring Rules and STV.
Axiomatic Characterization of Game-Theoretic Network Centralities.
Constrained Pure Nash Equilibria in Polymatrix Games.
Mechanism Design for Multi-Type Housing Markets.
Achieving Sustainable Cooperation in Generalized Prisoner's Dilemma with Observation Errors.
Proportional Justified Representation.
Luis Sánchez Fernández Edith Elkind Martin Lackner Norberto Fernández García Jesús Arias-Fisteus Pablo Basanta-Val Piotr Skowron
Revenue Maximization for Finitely Repeated Ad Auctions.
Psychological Forest: Predicting Human Behavior.
Preferences Single-Peaked on a Circle.
Recognising Multidimensional Euclidean Preferences.
Tractable Algorithms for Approximate Nash Equilibria in Generalized Graphical Games with Tree Structure.
On Covering Codes and Upper Bounds for the Dimension of Simple Games.
Optimal Pricing for Submodular Valuations with Bounded Curvature.
An Ambiguity Aversion Model for Decision Making under Ambiguity.
Sequential Peer Prediction: Learning to Elicit Effort using Posted Prices.
Network, Popularity and Social Cohesion: A Game-Theoretic Approach.
Optimal Personalized Defense Strategy Against Man-In-The-Middle Attack.
Mechanism Design in Social Networks.
Complexity of the Stable Invitations Problem.
Resource Graph Games: A Compact Representation for Games with Structured Strategy Spaces.
Group Activity Selection on Social Networks.
Heuristic Search Value Iteration for One-Sided Partially Observable Stochastic Games.
Computing Least Cores of Supermodular Cooperative Games.
Vote Until Two of You Agree: Mechanisms with Small Distortion and Sample Complexity.
Engineering Agreement: The Naming Game with Asymmetric and Heterogeneous Agents.
Security Games on a Plane.
Crowdsourced Outcome Determination in Prediction Markets.
Obvious Strategyproofness Needs Monitoring for Good Approximations.
Selfish Knapsack.
Extensive-Form Perfect Equilibrium Computation in Two-Player Games.
What Do Multiwinner Voting Rules Do? An Experiment Over the Two-Dimensional Euclidean Domain.
Small Representations of Big Kidney Exchange Graphs.
The Complexity of Stable Matchings under Substitutable Preferences.
Disarmament Games.
The Computational Complexity of Weighted Greedy Matching.
Approximation and Parameterized Complexity of Minimax Approval Voting.
Winner Determination in Huge Elections with MapReduce.
Bounded Rationality of Restricted Turing Machines.
On Markov Games Played by Bayesian and Boundedly-Rational Players.
Optimizing Positional Scoring Rules for Rank Aggregation.
Dynamic Thresholding and Pruning for Regret Minimization.
Multiwinner Approval Rules as Apportionment Methods.
Phragmén's Voting Methods and Justified Representation.
Probably Approximately Efficient Combinatorial Auctions via Machine Learning.
Teams in Online Scheduling Polls: Game-Theoretic Aspects.
Exclusion Method for Finding Nash Equilibrium in Multiplayer Games.
Preference Elicitation For Participatory Budgeting.
Faster and Simpler Algorithm for Optimal Strategies of Blotto Game.
A Study of Compact Reserve Pricing Languages.
Team-Maxmin Equilibrium: Efficiency Bounds and Algorithms.
On Pareto Optimality in Social Distance Games.
Nash Stability in Social Distance Games.
Algorithms for Max-Min Share Fair Allocation of Indivisible Chores.
Complexity of Manipulating Sequential Allocation.
Strategic Signaling and Free Information Disclosure in Auctions.
Envy-Free Mechanisms with Minimum Number of Cuts.
Incentivising Monitoring in Open Normative Systems.
Automated Design of Robust Mechanisms.
Market Pricing for Data Streams.
The Efficiency of the HyperPlay Technique Over Random Sampling.
An Integrated Model for Effective Saliency Prediction.
Associative Memory Using Dictionary Learning and Expander Decoding.
Expectile Matrix Factorization for Skewed Data Analysis.
Efficient Delivery Policy to Minimize User Traffic Consumption in Guaranteed Advertising.
Finding Critical Users for Social Network Engagement: The Collapsed k-Core Problem.
Correlated Cascades: Compete or Cooperate.
Visual Sentiment Analysis by Attending on Local Image Regions.
Learning Visual Sentiment Distributions via Augmented Conditional Probability Neural Network.
Multiple Source Detection without Knowing the Underlying Propagation Model.
CLARE: A Joint Approach to Label Classification and Tag Recommendation.
Community Preserving Network Embedding.
Phrase-Based Presentation Slides Generation for Academic Papers.
Exploiting both Vertical and Horizontal Dimensions of Feature Hierarchy for Effective Recommendation.
Web-Based Semantic Fragment Discovery for On-Line Lingual-Visual Similarity.
Radon - Rapid Discovery of Topological Relations.
Understanding the Semantic Structures of Tables with a Hybrid Deep Neural Network Architecture.
Multi-Task Deep Learning for User Intention Understanding in Speech Interaction Systems.
Semantic Proximity Search on Heterogeneous Graph by Proximity Embedding.
A Declarative Approach to Data-Driven Fact Checking.
Treatment Effect Estimation with Data-Driven Variable Decomposition.
Read the Silence: Well-Timed Recommendation via Admixture Marked Point Processes.
Random-Radius Ball Method for Estimating Closeness Centrality.
Joint Identification of Network Communities and Semantics via Integrative Modeling of Network Topologies and Node Contents.
A Dependency-Based Neural Reordering Model for Statistical Machine Translation.
POI2Vec: Geographical Latent Representation for Predicting Future Visitors.
TweetFit: Fusing Multiple Social Media and Sensor Data for Wellness Profile Learning.
Marrying Uncertainty and Time in Knowledge Graphs.
Transitive Hashing Network for Heterogeneous Multimedia Retrieval.
StructInf: Mining Structural Influence from Social Streams.
Volumetric ConvNets with Mixed Residual Connections for Automated Prostate Segmentation from 3D MR Images.
Local Discriminant Hyperalignment for Multi-Subject fMRI Data Alignment.
Gated Neural Networks for Option Pricing: Rationality by Design.
Profit-Driven Team Grouping in Social Networks.
Towards Better Understanding the Clothing Fashion Styles: A Multimodal Deep Learning Approach.
Novel Geometric Approach for Global Alignment of PPI Networks.
Partitioned Sampling of Public Opinions Based on Their Social Dynamics.
A Leukocyte Detection Technique in Blood Smear Images Using Plant Growth Simulation Algorithm.
Taming the Matthew Effect in Online Markets with Social Influence.
SnapNETS: Automatic Segmentation of Network Sequences with Node Labels.