aaai 2016 论文列表
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, February 12-17, 2016, Phoenix, Arizona, USA.
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Productive Aging through Intelligent Personalized Crowdsourcing.
Information Credibility Evaluation on Social Media.
SAPE: A System for Situation-Aware Public Security Evaluation.
Shoot to Know What: An Application of Deep Networks on Mobile Devices.
Markov Argumentation Random Fields.
DECT: Distributed Evolving Context Tree for Understanding User Behavior Pattern Evolution.
A Fraud Resilient Medical Insurance Claim System.
Multi-Agent System Development MADE Easy.
A Visual Semantic Framework for Innovation Analytics.
A Tool to Graphically Edit CP-Nets.
EDDIE: An Embodied AI System for Research and Intervention for Individuals with ASD.
Toward Interactive Relational Learning.
Artificial Swarm Intelligence, a Human-in-the-Loop Approach to A.I.
WWDS APIs: Application Programming Interfaces for Efficient Manipulation of World WordNet Database Structure.
Jikan to Kukan: A Hands-On Musical Experience in AI, Games and Art.
An Image Analysis Environment for Species Identification of Food Contaminating Beetles.
Write-righter: An Academic Writing Assistant System.
Moodee: An Intelligent Mobile Companion for Sensing Your Stress from Your Social Media Postings.
BBookX: Building Online Open Books for Personalized Learning.
EKNOT: Event Knowledge from News and Opinions in Twitter.
Predicting Personal Traits from Facial Images Using Convolutional Neural Networks Augmented with Facial Landmark Information.
Using Convolutional Neural Networks to Analyze Function Properties from Images.
Modeling and Experimentation Framework for Fuzzy Cognitive Maps.
NLU Framework for Voice Enabling Non-Native Applications on Smart Devices.
Predicting Gaming Related Properties from Twitter Accounts.
Deploying PAWS to Combat Poaching: Game-Theoretic Patrolling in Areas with Complex Terrain (Demonstration).
SVVAMP: Simulator of Various Voting Algorithms in Manipulating Populations.
co-rank: An Online Tool for Collectively Deciding Efficient Rankings Among Peers.
Artificial Intelligence for Predictive and Evidence Based Architecture Design.
What's Hot at RoboCup.
Competition of Distributed and Multiagent Planners (CoDMAP).
What's Hot in Heuristic Search.
Angry Birds as a Challenge for Artificial Intelligence.
General Video Game AI: Competition, Challenges and Opportunities.
What's Hot in Intelligent User Interfaces.
Inductive Logic Programming: Challenges.
What's Hot in the Answer Set Programming Competition.
What's Hot in Human Language Technology: Highlights from NAACL HLT 2015.
Affective Computing and Applications of Image Emotion Perceptions.
Architectural Mechanisms for Situated Natural Language Understanding in Uncertain and Open Worlds.
Pragmatic Querying in Heterogeneous Knowledge Graphs.
Adapting Plans through Communication with Unknown Teammates.
Scaling-Up MAP and Marginal MAP Inference in Markov Logic.
Writing Stories with Help from Recurrent Neural Networks.
Analogical Generalization of Linguistic Constructions.
Robust Classification under Covariate Shift with Application to Active Learning.
Estimating Text Intelligibility via Information Packaging Analysis.
Unsupervised Learning of HTNs in Complex Adversarial Domains.
Multi-Modal Learning over User-Contributed Content from Cross-Domain Social Media.
Privacy Management in Agent-Based Social Networks.
Apprenticeship Scheduling for Human-Robot Teams.
Integrating Planning and Recognition to Close the Interaction Loop.
Robust Learning from Demonstration Techniques and Tools.
Machine Learning for Computational Psychology.
Interactive Learning and Analogical Chaining for Moral and Commonsense Reasoning.
Learning Structural Features of Nodes in Large-Scale Networks for Link Prediction.
User-Centric Affective Computing of Image Emotion Perceptions.
Intrinsic and Extrinsic Evaluations of Word Embeddings.
MicroScholar: Mining Scholarly Information from Chinese Microblogs.
Epitomic Image Super-Resolution.
Mobility Sequence Extraction and Labeling Using Sparse Cell Phone Data.
Direct Discriminative Bag Mapping for Multi-Instance Learning.
Business Event Curation: Merging Human and Automated Approaches.
Text Simplification Using Neural Machine Translation.
Evaluating the Robustness of Game Theoretic Solutions When Using Abstraction.
Image Privacy Prediction Using Deep Features.
Abstracting Complex Domains Using Modular Object-Oriented Markov Decision Processes.
ROOT13: Spotting Hypernyms, Co-Hyponyms and Randoms.
Unsupervised Measure of Word Similarity: How to Outperform Co-Occurrence and Vector Cosine in VSMs.
Discriminative Structure Learning of Arithmetic Circuits.
Counter-Transitivity in Argument Ranking Semantics.
Heuristic Planning for Hybrid Systems.
Towards Structural Tractability in Hedonic Games.
SPAN: Understanding a Question with Its Support Answers.
Efficient Collaborative Crowdsourcing.
Human-Robot Trust and Cooperation Through a Game Theoretic Framework.
Bayesian AutoEncoder: Generation of Bayesian Networks with Hidden Nodes for Features.
Conquering Adversary Behavioral Uncertainty in Security Games: An Efficient Modeling Robust Based Algorithm.
A Word Embedding and a Josa Vector for Korean Unsupervised Semantic Role Induction.
Pseudo-Tree Construction Heuristics for DCOPs with Variable Communication Times.
Iterative Project Quasi-Newton Algorithm for Training RBM.
Decision Sum-Product-Max Networks.
Two-Stream Contextualized CNN for Fine-Grained Image Classification.
Social Emotion Classification via Reader Perspective Weighted Model.
Predicting Links and Their Building Time: A Path-Based Approach.
Handling Class Imbalance in Link Prediction Using Learning to Rank Techniques.
Hierarchy Prediction in Online Communities.
Monte Carlo Tree Search for Multi-Robot Task Allocation.
Connecting the Dots Using Contextual Information Hidden in Text and Images.
Learning Complex Stand-Up Motion for Humanoid Robots.
Multivariate Conditional Outlier Detection and Its Clinical Application.
Structure Aware L1 Graph for Data Clustering.
Authorship Attribution Using a Neural Network Language Model.
Trust and Distrust Across Coalitions: Shapley Value Based Centrality Measures for Signed Networks (Student Abstract Version).
A Comparison of Supervised Learning Algorithms for Telerobotic Control Using Electromyography Signals.
Robust Execution Strategies for Probabilistic Temporal Planning.
Predicting Prices in the Power TAC Wholesale Energy Market.
A CP-Based Approach for Popular Matching.
BRBA: A Blocking-Based Association Rule Hiding Method.
Bayesian Markov Games with Explicit Finite-Level Types.
Abstraction Using Analysis of Subgames.
Weighted A* Algorithms for Unsupervised Feature Selection with Provable Bounds on Suboptimality.
MIP-Nets: Enabling Information Sharing in Loosely-Coupled Teamwork.
Rational Verification: From Model Checking to Equilibrium Checking.
Strategic Behaviour When Allocating Indivisible Goods.
Natural Language Processing for Enhancing Teaching and Learning.
Ontology Instance Linking: Towards Interlinked Knowledge Graphs.
Ethical Dilemmas for Adaptive Persuasion Systems.
Five Dimensions of Reasoning in the Wild.
Embedding Ethical Principles in Collective Decision Support Systems.
Indefinite Scalability for Living Computation.
Model AI Assignments 2016.
Training Watson - A Cognitive Systems Course.
Teaching Automated Strategic Reasoning Using Capstone Tournaments.
Using Declarative Programming in an Introductory Computer Science Course for High School Students.
An Online Logic Programming Development Environment.
A.I. as an Introduction to Research Methods in Computer Science.
IRobot: Teaching the Basics of Artificial Intelligence in High Schools.
A Survey of Current Practice and Teaching of AI.
The Turing Test in the Classroom.
From the Lab to the Classroom and Beyond: Extending a Game-Based Research Platform for Teaching AI to Diverse Audiences.
Creating Interactive and Visual Educational Resources for AI.
Learning and Using Hand Abstraction Values for Parameterized Poker Squares.
Design of an Online Course on Knowledge-Based AI.
Teaching Big Data Analytics Skills with Intelligent Workflow Systems.
Conceptualizing Curse of Dimensionality with Parallel Coordinates.
BeeMo, a Monte Carlo Simulation Agent for Playing Parameterized Poker Squares.
Using Domain Knowledge to Improve Monte-Carlo Tree Search Performance in Parameterized Poker Squares.
Infusing Human Factors into Algorithmic Crowdsourcing.
A Hidden Markov Model Approach to Infer Timescales for High-Resolution Climate Archives.
Automated Volumetric Intravascular Plaque Classification Using Optical Coherence Tomography (OCT).
Data Driven Game Theoretic Cyber Threat Mitigation.
MetaSeer.STEM: Towards Automating Meta-Analyses.
Automated Capture and Execution of Manufacturability Rules Using Inductive Logic Programming.
Optimizing Energy Costs in a Zinc and Lead Mine.
Wikipedia in the Tourism Industry: Forecasting Demand and Modeling Usage Behavior.
Automated Regression Testing Using Constraint Programming.
Data-Augmented Software Diagnosis.
Document Type Classification in Online Digital Libraries.
An Autonomous Override System to Prevent Airborne Loss of Control.
Deploying nEmesis: Preventing Foodborne Illness by Data Mining Social Media.
Ontology Re-Engineering: A Case Study from the Automotive Industry.
Deploying PAWS: Field Optimization of the Protection Assistant for Wildlife Security.
A Framework for Resolving Open-World Referential Expressions in Distributed Heterogeneous Knowledge Bases.
Affective Personalization of a Social Robot Tutor for Children's Second Language Skills.
Bagging Ensembles for the Diagnosis and Prognostication of Alzheimer's Disease.
An Algorithm to Coordinate Measurements Using Stochastic Human Mobility Patterns in Large-Scale Participatory Sensing Settings.
Transfer Learning from Deep Features for Remote Sensing and Poverty Mapping.
Optimizing Resilience in Large Scale Networks.
Adaptable Regression Method for Ensemble Consensus Forecasting.
Intelligent Habitat Restoration Under Uncertainty.
Predicting Spatio-Temporal Propagation of Seasonal Influenza Using Variational Gaussian Process Regression.
Benders Decomposition for Large-Scale Prescriptive Evacuations.
Big-Data Mechanisms and Energy-Policy Design.
Preventing Illegal Logging: Simultaneous Optimization of Resource Teams and Tactics for Security.
Spatially Regularized Streaming Sensor Selection.
Optimizing Infrastructure Enhancements for Evacuation Planning.
Robust Decision Making for Stochastic Network Design.
Shortest Path Based Decision Making Using Probabilistic Inference.
Energy- and Cost-Efficient Pumping Station Control.
Topic Models to Infer Socio-Economic Maps.
A Unifying Variational Inference Framework for Hierarchical Graph-Coupled HMM with an Application to Influenza Infection.
Understanding Dominant Factors for Precipitation over the Great Lakes Region.
Multiagent-Based Route Guidance for Increasing the Chance of Arrival on Time.
Multi-Instance Multi-Label Class Discovery: A Computational Approach for Assessing Bird Biodiversity.
An Axiomatic Framework for Ex-Ante Dynamic Pricing Mechanisms in Smart Grid.
Understanding City Traffic Dynamics Utilizing Sensor and Textual Observations.
Achieving Stable and Fair Profit Allocation with Minimum Subsidy in Collaborative Logistics.
Building End-To-End Dialogue Systems Using Generative Hierarchical Neural Network Models.
QART: A System for Real-Time Holistic Quality Assurance for Contact Center Dialogues.
Unsupervised Lexical Simplification for Non-Native Speakers.
Modeling Human Understanding of Complex Intentional Action with a Bayesian Nonparametric Subgoal Model.
Predicting Readers' Sarcasm Understandability by Modeling Gaze Behavior.
Modeling Human Ad Hoc Coordination.
Visual Learning of Arithmetic Operation.
Surprise-Triggered Reformulation of Design Goals.
Commonsense Interpretation of Triangle Behavior.
MIDCA: A Metacognitive, Integrated Dual-Cycle Architecture for Self-Regulated Autonomy.
Using Multiple Representations to Simultaneously Learn Computational Thinking and Middle School Science.
Co-Occurrence Feature Learning for Skeleton Based Action Recognition Using Regularized Deep LSTM Networks.
MC-HOG Correlation Tracking with Saliency Proposal.
Learning Cross-Domain Neural Networks for Sketch-Based 3D Shape Retrieval.
Group Cost-Sensitive Boosting for Multi-Resolution Pedestrian Detection.
Discrete Image Hashing Using Large Weakly Annotated Photo Collections.
Unsupervised Co-Activity Detection from Multiple Videos Using Absorbing Markov Chain.
Large Scale Similarity Learning Using Similar Pairs for Person Verification.
Metric Embedded Discriminative Vocabulary Learning for High-Level Person Representation.
Diversified Dynamical Gaussian Process Latent Variable Model for Video Repair.
Pose-Guided Human Parsing by an AND/OR Graph Using Pose-Context Features.
Path Following with Adaptive Path Estimation for Graph Matching.
Video Semantic Clustering with Sparse and Incomplete Tags.
DARI: Distance Metric and Representation Integration for Person Verification.
Recognizing Actions in 3D Using Action-Snippets and Activated Simplices.
Domain-Constraint Transfer Coding for Imbalanced Unsupervised Domain Adaptation.
Toward a Taxonomy and Computational Models of Abnormalities in Images.
Look, Listen and Learn - A Multimodal LSTM for Speaker Identification.
SentiCap: Generating Image Descriptions with Sentiments.
Learning to Answer Questions from Image Using Convolutional Neural Network.
Face Model Compression by Distilling Knowledge from Neurons.
Multi-View 3D Human Tracking in Crowded Scenes.
Articulated Pose Estimation Using Hierarchical Exemplar-Based Models.
Decentralized Robust Subspace Clustering.
Labeling the Features Not the Samples: Efficient Video Classification with Minimal Supervision.
Exploiting View-Specific Appearance Similarities Across Classes for Zero-Shot Pose Prediction: A Metric Learning Approach.
Robust Complex Behaviour Modeling at 90Hz.
Structured Output Prediction for Semantic Perception in Autonomous Vehicles.
Reading Scene Text in Deep Convolutional Sequences.
Transductive Zero-Shot Recognition via Shared Model Space Learning.
Concepts Not Alone: Exploring Pairwise Relationships for Zero-Shot Video Activity Recognition.
Zero-Shot Event Detection by Multimodal Distributional Semantic Embedding of Videos.
Face Video Retrieval via Deep Learning of Binary Hash Representations.
Dynamic Concept Composition for Zero-Example Event Detection.
Deep Quantization Network for Efficient Image Retrieval.
Are Elephants Bigger than Butterflies? Reasoning about Sizes of Objects.
Counting-Based Search for Constraint Optimization Problems.
Exponential Recency Weighted Average Branching Heuristic for SAT Solvers.
Increasing Nogoods in Restart-Based Search.
Breaking More Composition Symmetries Using Search Heuristics.
Bidirectional Search That Is Guaranteed to Meet in the Middle.
On the Extraction of One Maximal Information Subset That Does Not Conflict with Multiple Contexts.
Using the Shapley Value to Analyze Algorithm Portfolios.
Alternative Filtering for the Weighted Circuit Constraint: Comparing Lower Bounds for the TSP and Solving TSPTW.
Steiner Tree Problems with Side Constraints Using Constraint Programming.
The Meta-Problem for Conservative Mal'tsev Constraints.
Component Caching in Hybrid Domains with Piecewise Polynomial Densities.
Deep Tracking: Seeing Beyond Seeing Using Recurrent Neural Networks.
Selectively Reactive Coordination for a Team of Robot Soccer Champions.
Continual Planning in Golog.
Efficient Spatio-Temporal Tactile Object Recognition with Randomized Tiling Convolutional Networks in a Hierarchical Fusion Strategy.
Distance Minimization for Reward Learning from Scored Trajectories.
Closing the Gap Between Short and Long XORs for Model Counting.
Separators and Adjustment Sets in Markov Equivalent DAGs.
RAO*: An Algorithm for Chance-Constrained POMDP's.
Learning Ensembles of Cutset Networks.
Learning Bayesian Networks with Bounded Tree-width via Guided Search.
Closed-Form Gibbs Sampling for Graphical Models with Algebraic Constraints.
Scaling Relational Inference Using Proofs and Refutations.
Online Spatio-Temporal Matching in Stochastic and Dynamic Domains.
On Learning Causal Models from Relational Data.
From Exact to Anytime Solutions for Marginal MAP.
Exact Sampling with Integer Linear Programs and Random Perturbations.
On Parameter Tying by Quantization.
Structured Features in Naive Bayes Classification.
A Symbolic SAT-Based Algorithm for Almost-Sure Reachability with Small Strategies in POMDPs.
Approximate Probabilistic Inference via Word-Level Counting.
Approximation Algorithms for Route Planning with Nonlinear Objectives.
A POMDP Formulation of Proactive Learning.
A Proactive Sampling Approach to Project Scheduling under Uncertainty.
Efficient Macroscopic Urban Traffic Models for Reducing Congestion: A PDDL+ Planning Approach.
Solving Goal Recognition Design Using ASP.
Solving Transition-Independent Multi-Agent MDPs with Sparse Interactions.
Multi-Agent Path Finding with Payload Transfers and the Package-Exchange Robot-Routing Problem.
Computing Contingent Plans Using Online Replanning.
Goal Recognition Design with Non-Observable Actions.
Randomised Procedures for Initialising and Switching Actions in Policy Iteration.
Solving Risk-Sensitive POMDPs With and Without Cost Observations.
General Error Bounds in Heuristic Search Algorithms for Stochastic Shortest Path Problems.
Truncated Approximate Dynamic Programming with Task-Dependent Terminal Value.
Dynamic Controllability of Disjunctive Temporal Networks: Validation and Synthesis of Executable Strategies.
Aggregating Inter-Sentence Information to Enhance Relation Extraction.
A Joint Model for Entity Set Expansion and Attribute Extraction from Web Search Queries.
A Joint Model for Question Answering over Multiple Knowledge Bases.
Gated Neural Networks for Targeted Sentiment Analysis.
Tweet Timeline Generation with Determinantal Point Processes.
Exploring Multiple Feature Spaces for Novel Entity Discovery.
Improving Recommendation of Tail Tags for Questions in Community Question Answering.
Personalized Microblog Sentiment Classification via Multi-Task Learning.
Identifying Search Keywords for Finding Relevant Social Media Posts.
Temporal Topic Analysis with Endogenous and Exogenous Processes.
Improving Twitter Sentiment Classification Using Topic-Enriched Multi-Prototype Word Embeddings.
Discovering User Attribute Stylistic Differences via Paraphrasing.
A Semi-Supervised Learning Approach to Why-Question Answering.
Microsummarization of Online Reviews: An Experimental Study.
Joint Word Segmentation, POS-Tagging and Syntactic Chunking.
Reading the Videos: Temporal Labeling for Crowdsourced Time-Sync Videos Based on Semantic Embedding.
A Probabilistic Soft Logic Based Approach to Exploiting Latent and Global Information in Event Classification.
Improving Opinion Aspect Extraction Using Semantic Similarity and Aspect Associations.
Argument Mining from Speech: Detecting Claims in Political Debates.
News Verification by Exploiting Conflicting Social Viewpoints in Microblogs.
Topical Analysis of Interactions Between News and Social Media.
Extracting Topical Phrases from Clinical Documents.
Global Distant Supervision for Relation Extraction.
To Swap or Not to Swap? Exploiting Dependency Word Pairs for Reordering in Statistical Machine Translation.
Acquiring Knowledge of Affective Events from Blogs Using Label Propagation.
Age of Exposure: A Model of Word Learning.
Discourse Relations Detection via a Mixed Generative-Discriminative Framework.
Joint Inference over a Lightly Supervised Information Extraction Pipeline: Towards Event Coreference Resolution for Resource-Scarce Languages.
TGSum: Build Tweet Guided Multi-Document Summarization Dataset.
Distant IE by Bootstrapping Using Lists and Document Structure.
Collective Supervision of Topic Models for Predicting Surveys with Social Media.
Labeling the Semantic Roles of Commas.
Semi-Supervised Multinomial Naive Bayes for Text Classification by Leveraging Word-Level Statistical Constraint.
Building Earth Mover's Distance on Bilingual Word Embeddings for Machine Translation.
A Morphology-Aware Network for Morphological Disambiguation.
Syntactic Skeleton-Based Translation.
Minimally-Constrained Multilingual Embeddings via Artificial Code-Switching.
Morphological Segmentation with Window LSTM Neural Networks.
A Deep Architecture for Semantic Matching with Multiple Positional Sentence Representations.
Non-Linear Similarity Learning for Compositionality.
Inside Out: Two Jointly Predictive Models for Word Representations and Phrase Representations.
Evaluation of Semantic Dependency Labeling Across Domains.
Inferring Interpersonal Relations in Narrative Summaries.
Learning Statistical Scripts with LSTM Recurrent Neural Networks.
Text Matching as Image Recognition.
Siamese Recurrent Architectures for Learning Sentence Similarity.
Addressing a Question Answering Challenge by Combining Statistical Methods with Inductive Rule Learning and Reasoning.
Listen, Attend, and Walk: Neural Mapping of Navigational Instructions to Action Sequences.
Numerical Relation Extraction with Minimal Supervision.
Convolution Kernels for Discriminative Learning from Streaming Text.
Implicit Discourse Relation Classification via Multi-Task Neural Networks.
Character-Aware Neural Language Models.
A Representation Learning Framework for Multi-Source Transfer Parsing.
What Happens Next? Event Prediction Using a Compositional Neural Network Model.
Extracting Biomolecular Interactions Using Semantic Parsing of Biomedical Text.
Jointly Modeling Topics and Intents with Global Order Structure.
Modeling Evolving Relationships Between Characters in Literary Novels.
Ask, and Shall You Receive? Understanding Desire Fulfillment in Natural Language Text.
Joint Word Representation Learning Using a Corpus and a Semantic Lexicon.
Instructable Intelligent Personal Agent.
PEAK: Pyramid Evaluation via Automated Knowledge Extraction.
Hashtag-Based Sub-Event Discovery Using Mutually Generative LDA in Twitter.
Representation Learning of Knowledge Graphs with Entity Descriptions.
Complementing Semantic Roles with Temporally Anchored Spatial Knowledge: Crowdsourced Annotations and Experiments.
Dependency Tree Representations of Predicate-Argument Structures.
Fine-Grained Semantic Conceptualization of FrameNet.
Agreement on Target-Bidirectional LSTMs for Sequence-to-Sequence Learning.
A Generative Model of Words and Relationships from Multiple Sources.
Representing Verbs as Argument Concepts.
Single or Multiple? Combining Word Representations Independently Learned from Text and WordNet.
A Unified Bayesian Model of Scripts, Frames and Language.
ExTaSem! Extending, Taxonomizing and Semantifying Domain Terminologies.
Verb Pattern: A Probabilistic Semantic Representation on Verbs.
Combining Retrieval, Statistics, and Inference to Answer Elementary Science Questions.
Topic Concentration in Query Focused Summarization Datasets.
Short Text Representation for Detecting Churn in Microblogs.
Robust Execution of BDI Agent Programs by Exploiting Synergies Between Intentions.
Is It Harmful When Advisors Only Pretend to Be Honest?
ConTaCT: Deciding to Communicate during Time-Critical Collaborative Tasks in Unknown, Deterministic Domains.
Exploiting Anonymity in Approximate Linear Programming: Scaling to Large Multiagent MDPs.
Bayesian Learning of Other Agents' Finite Controllers for Interactive POMDPs.
Learning for Decentralized Control of Multiagent Systems in Large, Partially-Observable Stochastic Environments.
Model Checking Probabilistic Knowledge: A PSPACE Case.
Strengthening Agents Strategic Ability with Communication.
Efficient Computation of Emergent Equilibrium in Agent-Based Simulation.
Emergence of Social Punishment and Cooperation through Prior Commitments.
Implicit Coordination in Crowded Multi-Agent Navigation.
Multi-Variable Agents Decomposition for DCOPs.
Target Surveillance in Adversarial Environments Using POMDPs.
Frugal Bribery in Voting.
Global Model Checking on Pushdown Multi-Agent Systems.
Complexity of Shift Bribery in Committee Elections.
Detection of Plan Deviation in Multi-Agent Systems.
Temporal Vaccination Games under Resource Constraints.
Stochastic Parallel Block Coordinate Descent for Large-Scale Saddle Point Problems.
Coupled Dictionary Learning for Unsupervised Feature Selection.
Deep Hashing Network for Efficient Similarity Retrieval.
Veto-Consensus Multiple Kernel Learning.
Transfer Learning for Cross-Language Text Categorization through Active Correspondences Construction.
Fast Nonsmooth Regularized Risk Minimization with Continuation.
DinTucker: Scaling Up Gaussian Process Models on Large Multidimensional Arrays.
Fast Asynchronous Parallel Stochastic Gradient Descent: A Lock-Free Approach with Convergence Guarantee.
A Scalable and Extensible Framework for Superposition-Structured Models.
On the Differential Privacy of Bayesian Inference.
Multi-Domain Active Learning for Recommendation.
Near-Optimal Active Learning of Multi-Output Gaussian Processes.
Large-Scale Graph-Based Semi-Supervised Learning via Tree Laplacian Solver.
Accelerated Sparse Linear Regression via Random Projection.
An Alternating Proximal Splitting Method with Global Convergence for Nonconvex Structured Sparsity Optimization.
Asynchronous Distributed Semi-Stochastic Gradient Optimization.
Stochastic Optimization for Kernel PCA.
Learning Expected Hitting Time Distance.
A Proximal Alternating Direction Method for Semi-Definite Rank Minimization.
On Order-Constrained Transitive Distance Clustering.
Derivative-Free Optimization via Classification.
Scalable Completion of Nonnegative Matrix with Separable Structure.
Instance Specific Metric Subspace Learning: A Bayesian Approach.
Learning Continuous-Time Bayesian Networks in Relational Domains: A Non-Parametric Approach.
Efficient Average Reward Reinforcement Learning Using Constant Shifting Values.
Analysis-Synthesis Dictionary Learning for Universality-Particularity Representation Based Classification.
Robust Semi-Supervised Learning through Label Aggregation.
Representing Sets of Instances for Visual Recognition.
Constrained Submodular Minimization for Missing Labels and Class Imbalance in Multi-label Learning.
Model-Free Preference-Based Reinforcement Learning.
Unsupervised Feature Selection on Networks: A Generative View.
Nonlinear Feature Extraction with Max-Margin Data Shifting.
Adaptive Normalized Risk-Averting Training for Deep Neural Networks.
Learning Deep ℓ0 Encoders.
Learning by Transferring from Unsupervised Universal Sources.
Noise-Adaptive Margin-Based Active Learning and Lower Bounds under Tsybakov Noise Condition.
Toward a Better Understanding of Deep Neural Network Based Acoustic Modelling: An Empirical Investigation.
Co-Regularized PLSA for Multi-Modal Learning.
An Efficient Time Series Subsequence Pattern Mining and Prediction Framework with an Application to Respiratory Motion Prediction.
Optimizing Multivariate Performance Measures from Multi-View Data.
Relational Knowledge Transfer for Zero-Shot Learning.
Semi-Supervised Dictionary Learning via Structural Sparse Preserving.
Text Classification with Heterogeneous Information Network Kernels.
Product Grassmann Manifold Representation and Its LRR Models.
Multitask Generalized Eigenvalue Program.
The Hidden Convexity of Spectral Clustering.
Online Instrumental Variable Regression with Applications to Online Linear System Identification.
Deep Reinforcement Learning with Double Q-Learning.
Algorithms for Differentially Private Multi-Armed Bandits.
Learning Sparse Confidence-Weighted Classifier on Very High Dimensional Data.
Linear-Time Learning on Distributions with Approximate Kernel Embeddings.
On the Depth of Deep Neural Networks: A Theoretical View.
Return of Frustratingly Easy Domain Adaptation.
Marginalized Continuous Time Bayesian Networks for Network Reconstruction from Incomplete Observations.
Bayesian Matrix Completion via Adaptive Relaxed Spectral Regularization.
Noisy Submodular Maximization via Adaptive Sampling with Applications to Crowdsourced Image Collection Summarization.
Metric Learning for Ordinal Data.
Spectral Bisection Tree Guided Deep Adaptive Exemplar Autoencoder for Unsupervised Domain Adaptation.
Scalable Algorithms for Tractable Schatten Quasi-Norm Minimization.
Selecting Near-Optimal Learners via Incremental Data Allocation.
Scaling Simultaneous Optimistic Optimization for High-Dimensional Non-Convex Functions with Low Effective Dimensions.
Inverse Reinforcement Learning through Policy Gradient Minimization.
Viral Clustering: A Robust Method to Extract Structures in Heterogeneous Datasets.
Efficient PAC-Optimal Exploration in Concurrent, Continuous State MDPs with Delayed Updates.
The Constrained Laplacian Rank Algorithm for Graph-Based Clustering.
New l1-Norm Relaxations and Optimizations for Graph Clustering.
Holographic Embeddings of Knowledge Graphs.
All-in Text: Learning Document, Label, and Word Representations Jointly.
Fixed-Rank Supervised Metric Learning on Riemannian Manifold.
Reinforcement Learning with Parameterized Actions.
Offline Evaluation of Online Reinforcement Learning Algorithms.
Expected Tensor Decomposition with Stochastic Gradient Descent.
Sparse Latent Space Policy Search.
Learning FRAME Models Using CNN Filters.
Finding One's Best Crowd: Online Learning By Exploiting Source Similarity.
Multiple Kernel k-Means Clustering with Matrix-Induced Regularization.
Sparse Perceptron Decision Tree for Millions of Dimensions.
Consensus Guided Unsupervised Feature Selection.
Online ARIMA Algorithms for Time Series Prediction.
Gaussian Process Planning with Lipschitz Continuous Reward Functions: Towards Unifying Bayesian Optimization, Active Learning, and Beyond.
Interaction Point Processes via Infinite Branching Model.
Re-Active Learning: Active Learning with Relabeling.
How Important Is Weight Symmetry in Backpropagation?
Fast and Accurate Refined Nyström-Based Kernel SVM.
Accelerating Random Kaczmarz Algorithm Based on Clustering Information.
Towards Safe Semi-Supervised Learning for Multivariate Performance Measures.
Scalable Sequential Spectral Clustering.
Multi-Objective Self-Paced Learning.
High-Order Stochastic Gradient Thermostats for Bayesian Learning of Deep Models.
Preconditioned Stochastic Gradient Langevin Dynamics for Deep Neural Networks.
Compressed Conditional Mean Embeddings for Model-Based Reinforcement Learning.
Learning Future Classifiers without Additional Data.
Uncorrelated Group LASSO.
Bounded Optimal Exploration in MDP.
Shakeout: A New Regularized Deep Neural Network Training Scheme.
Delay-Tolerant Online Convex Optimization: Unified Analysis and Adaptive-Gradient Algorithms.
Deep Learning with S-Shaped Rectified Linear Activation Units.
Wishart Mechanism for Differentially Private Principal Components Analysis.
The l2, 1-Norm Stacked Robust Autoencoders for Domain Adaptation.
A Probabilistic Approach to Knowledge Translation.
Improving Predictive State Representations via Gradient Descent.
Infinite Plaid Models for Infinite Bi-Clustering.
Conservativeness of Untied Auto-Encoders.
Optimal Discrete Matrix Completion.
Multi-Label Manifold Learning.
Common and Discriminative Subspace Kernel-Based Multiblock Tensor Partial Least Squares Regression.
Discriminative Vanishing Component Analysis.
Flattening the Density Gradient for Eliminating Spatial Centrality to Reduce Hubness.
SAND: Semi-Supervised Adaptive Novel Class Detection and Classification over Data Stream.
Reduction Techniques for Graph-Based Convex Clustering.
Multi-Stage Multi-Task Learning with Reduced Rank.
Generalized Emphatic Temporal Difference Learning: Bias-Variance Analysis.
Active Learning with Cross-Class Knowledge Transfer.
Discriminative Analysis Dictionary Learning.
Teaching-to-Learn and Learning-to-Teach for Multi-label Propagation.
Uncertainty Propagation in Long-Term Structured Regression on Evolving Networks.
Extending the Modelling Capacity of Gaussian Conditional Random Fields while Learning Faster.
Assumed Density Filtering Methods for Learning Bayesian Neural Networks.
Decentralized Approximate Bayesian Inference for Distributed Sensor Network.
Risk Minimization in the Presence of Label Noise.
Group and Graph Joint Sparsity for Linked Data Classification.
Fast Lasso Algorithm via Selective Coordinate Descent.
Indexable Probabilistic Matrix Factorization for Maximum Inner Product Search.
The Ostomachion Process.
Random Composite Forests.
Generalised Brown Clustering and Roll-Up Feature Generation.
Reconstructing Hidden Permutations Using the Average-Precision (AP) Correlation Statistic.
Learning Step Size Controllers for Robust Neural Network Training.
Robustness of Bayesian Pool-Based Active Learning Against Prior Misspecification.
Knowledge Transfer with Interactive Learning of Semantic Relationships.
Progressive EM for Latent Tree Models and Hierarchical Topic Detection.
Maximum Margin Dirichlet Process Mixtures for Clustering.
Decoding Hidden Markov Models Faster Than Viterbi Via Online Matrix-Vector (max, +)-Multiplication.
Increasing the Action Gap: New Operators for Reinforcement Learning.
Incremental Stochastic Factorization for Online Reinforcement Learning.
Approximate K-Means++ in Sublinear Time.
Data Poisoning Attacks against Autoregressive Models.
Fast Hybrid Algorithm for Big Matrix Recovery.
Tracking Idea Flows between Social Groups.
Cold-Start Heterogeneous-Device Wireless Localization.
Pose-Dependent Low-Rank Embedding for Head Pose Estimation.
Learning a Hybrid Architecture for Sequence Regression and Annotation.
Collective Noise Contrastive Estimation for Policy Transfer Learning.
Simultaneous Feature and Sample Reduction for Image-Set Classification.
Semisupervised Autoencoder for Sentiment Analysis.
Submodular Asymmetric Feature Selection in Cascade Object Detection.
Linear Submodular Bandits with a Knapsack Constraint.
Learning Deep Convolutional Neural Networks for X-Ray Protein Crystallization Image Analysis.
Joint Multi-View Representation Learning and Image Tagging.
Factorization Ranking Model for Move Prediction in the Game of Go.
Efficient Nonparametric Subgraph Detection Using Tree Shaped Priors.
Exploiting an Oracle That Reports AUC Scores in Machine Learning Contests.
Instilling Social to Physical: Co-Regularized Heterogeneous Transfer Learning.
Recommending Groups to Users Using User-Group Engagement and Time-Dependent Matrix Factorization.
Drosophila Gene Expression Pattern Annotations via Multi-Instance Biological Relevance Learning.
Privacy-CNH: A Framework to Detect Photo Privacy with Convolutional Neural Network using Hierarchical Features.
Differential Privacy Preservation for Deep Auto-Encoders: an Application of Human Behavior Prediction.
Unsupervised Feature Selection with Structured Graph Optimization.
Learning Tractable Probabilistic Models for Fault Localization.
Convolutional Neural Networks over Tree Structures for Programming Language Processing.
Deep Learning for Algorithm Portfolios.
Learning Adaptive Forecasting Models from Irregularly Sampled Multivariate Clinical Data.
Recognizing Complex Activities by a Probabilistic Interval-Based Model.
Towards Optimal Binary Code Learning via Ordinal Embedding.
Learning with Marginalized Corrupted Features and Labels Together.
Random Mixed Field Model for Mixed-Attribute Data Restoration.
A Framework for Outlier Description Using Constraint Programming.
Column Sampling Based Discrete Supervised Hashing.
Consensus Style Centralizing Auto-Encoder for Weak Style Classification.
Learning to Appreciate the Aesthetic Effects of Clothing.
Efficient Learning of Timeseries Shapelets.
Creating Images by Learning Image Semantics Using Vector Space Models.
MOOCs Meet Measurement Theory: A Topic-Modelling Approach.
Graph-without-cut: An Ideal Graph Learning for Image Segmentation.
Robust Multi-View Subspace Learning through Dual Low-Rank Decompositions.
Seeing the Unseen Network: Inferring Hidden Social Ties from Respondent-Driven Sampling.
Deep Contextual Networks for Neuronal Structure Segmentation.
Mitosis Detection in Breast Cancer Histology Images via Deep Cascaded Networks.
Discriminative Nonparametric Latent Feature Relational Models with Data Augmentation.
Deep Neural Networks for Learning Graph Representations.
Towards Domain Adaptive Vehicle Detection in Satellite Image by Supervised Super-Resolution Transfer.
Bayesian Inference of Recursive Sequences of Group Activities from Tracks.
On the Performance of GoogLeNet and AlexNet Applied to Sketches.
Mapping Action Language BC to Logic Programs: A Characterization by Postulates.
Decidable Verification of Golog Programs over Non-Local Effect Actions.
Affinity Preserving Quantization for Hashing: A Vector Quantization Approach to Compact Learn Binary Codes.
Query Answering with Inconsistent Existential Rules under Stable Model Semantics.
Complexity Results and Algorithms for Extension Enforcement in Abstract Argumentation.
Expressive Recommender Systems through Normalized Nonnegative Models.
Metaphysics of Planning Domain Descriptions.
Scalable Training of Markov Logic Networks Using Approximate Counting.
Zero-Suppressed Sentential Decision Diagrams.
Ontology-Mediated Queries for NOSQL Databases.
'Knowing Whether' in Proper Epistemic Knowledge Bases.
Causal Explanation Under Indeterminism: A Sampling Approach.
Resistance to Corruption of Strategic Argumentation.
Basic Probabilistic Ontological Data Exchange with Existential Rules.
Agenda Separability in Judgment Aggregation.
A Model for Learning Description Logic Ontologies Based on Exact Learning.
Learning Abductive Reasoning Using Random Examples.
Locally Adaptive Translation for Knowledge Graph Embedding.
Knowledge Graph Completion with Adaptive Sparse Transfer Matrix.
SAT-to-SAT: Declarative Extension of SAT Solvers with New Propagators.
The Complexity of LTL on Finite Traces: Hard and Easy Fragments.
Using Decomposition-Parameters for QBF: Mind the Prefix!
Qualitative Spatio-Temporal Stream Reasoning with Unobservable Intertemporal Spatial Relations Using Landmarks.
Verifying ConGolog Programs on Bounded Situation Calculus Theories.
Logical Foundations of Privacy-Preserving Publishing of Linked Data.
On the Containment of SPARQL Queries under Entailment Regimes.
SDDs Are Exponentially More Succinct than OBDDs.
Beyond OWL 2 QL in OBDA: Rewritings and Approximations.
A Comparative Study of Ranking-Based Semantics for Abstract Argumentation.
Automated Verification and Tightening of Failure Propagation Models.
Explaining Inconsistency-Tolerant Query Answering over Description Logic Knowledge Bases.
A First-Order Logic of Probability and Only Knowing in Unbounded Domains.
A Semantical Analysis of Second-Order Propositional Modal Logic.
Boolean Functions with Ordered Domains in Answer Set Programming.
Generating CP-Nets Uniformly at Random.
Minimizing User Involvement for Learning Human Mobility Patterns from Location Traces.
Personalized Alert Agent for Optimal User Performance.
A Deep Choice Model.
Intelligent Advice Provisioning for Repeated Interaction.
An Oral Exam for Measuring a Dialog System's Capabilities.
Behavioral Experiments in Email Filter Evasion.
Submodular Optimization with Routing Constraints.
Relaxed Majorization-Minimization for Non-Smooth and Non-Convex Optimization.
Two Efficient Local Search Algorithms for Maximum Weight Clique Problem.
Linearized Alternating Direction Method with Penalization for Nonconvex and Nonsmooth Optimization.
DRIMUX: Dynamic Rumor Influence Minimization with User Experience in Social Networks.
On the Completeness of Best-First Search Variants That Use Random Exploration.
A Combinatorial Search Perspective on Diverse Solution Generation.
Implementing Troubleshooting with Batch Repair.
Towards Clause-Learning State Space Search: Learning to Recognize Dead-Ends.
Fast ADMM Algorithm for Distributed Optimization with Adaptive Penalty.
Combining Bounding Boxes and JPS to Prune Grid Pathfinding.
Fast Proximal Linearized Alternating Direction Method of Multiplier with Parallel Splitting.
Local Search for Hard SAT Formulas: The Strength of the Polynomial Law.
Learning to Branch in Mixed Integer Programming.
Abstract Zobrist Hashing: An Efficient Work Distribution Method for Parallel Best-First Search.
The Complexity Landscape of Decompositional Parameters for ILP.
Solving the Station Repacking Problem.
Look-Ahead with Mini-Bucket Heuristics for MPE.
Nested Monte Carlo Search for Two-Player Games.
CAPReS: Context Aware Persona Based Recommendation for Shoppers.
Tiebreaking Strategies for A* Search: How to Explore the Final Frontier.
Unsupervised Feature Selection by Heuristic Search with Provable Bounds on Suboptimality.
Optimizing Personalized Email Filtering Thresholds to Mitigate Sequential Spear Phishing Attacks.
Lift-Based Bidding in Ad Selection.
Quantitative Extensions of the Condorcet Jury Theorem with Strategic Agents.
Computing Optimal Monitoring Strategy for Detecting Terrorist Plots.
Computing Rational Decisions In Extensive Games With Limited Foresight.
Closeness Centrality for Networks with Overlapping Community Structure.
False-Name-Proof Locations of Two Facilities: Economic and Algorithmic Approaches.
Optimal Aggregation of Uncertain Preferences.
Fast Optimal Clearing of Capped-Chain Barter Exchanges.
Preferences Single-Peaked on Nice Trees.
Graphical Hedonic Games of Bounded Treewidth.
Complexity of Hedonic Games with Dichotomous Preferences.
Refining Subgames in Large Imperfect Information Games.
Reinstating Combinatorial Protections for Manipulation and Bribery in Single-Peaked and Nearly Single-Peaked Electorates.
On the Complexity of mCP-nets.
Optimizing Trading Assignments in Water Right Markets.
Counterfactual Regret Minimization in Sequential Security Games.
Multi-Defender Strategic Filtering Against Spear-Phishing Attacks.
Multi-Attribute Proportional Representation.
When Can the Maximin Share Guarantee Be Guaranteed?
Who Can Win a Single-Elimination Tournament?
Sequence-Form and Evolutionary Dynamics: Realization Equivalence to Agent Form and Logit Dynamics.
A Geometric Method to Construct Minimal Peer Prediction Mechanisms.
Variations on the Hotelling-Downs Model.
Ad Auctions and Cascade Model: GSP Inefficiency and Algorithms.
Multiwinner Analogues of the Plurality Rule: Axiomatic and Algorithmic Perspectives.
Price of Pareto Optimality in Hedonic Games.
Judgment Aggregation under Issue Dependencies.
Rules for Choosing Societal Tradeoffs.
Incentives for Strategic Behavior in Fisher Market Games.
Assignment and Pricing in Roommate Market.
Using Correlated Strategies for Computing Stackelberg Equilibria in Extensive-Form Games.
Strategy-Based Warm Starting for Regret Minimization in Games.
One Size Does Not Fit All: A Game-Theoretic Approach for Dynamically and Effectively Screening for Threats.
An Algorithmic Framework for Strategic Fair Division.
Learning Market Parameters Using Aggregate Demand Queries.
A Security Game Combining Patrolling and Alarm-Triggered Responses Under Spatial and Detection Uncertainties.
Strategyproof Peer Selection: Mechanisms, Analyses, and Experiments.
Blind, Greedy, and Random: Algorithms for Matching and Clustering Using Only Ordinal Information.
Maximizing Revenue with Limited Correlation: The Cost of Ex-Post Incentive Compatibility.
From Duels to Battlefields: Computing Equilibria of Blotto and Other Games.
Computing Possible and Necessary Equilibrium Actions (and Bipartisan Set Winners).
Poker-CNN: A Pattern Learning Strategy for Making Draws and Bets in Poker Games Using Convolutional Networks.
Reuse of Neural Modules for General Video Game Playing.
Autonomous Electricity Trading Using Time-of-Use Tariffs in a Competitive Market.
Learning Deep Representation from Big and Heterogeneous Data for Traffic Accident Inference.
Egocentric Video Search via Physical Interactions.
Learning the Preferences of Ignorant, Inconsistent Agents.
STELLAR: Spatial-Temporal Latent Ranking for Successive Point-of-Interest Recommendation.
Building a Large Scale Dataset for Image Emotion Recognition: The Fine Print and The Benchmark.
Understanding Emerging Spatial Entities.
Online Cross-Modal Hashing for Web Image Retrieval.
Cross-Lingual Taxonomy Alignment with Bilingual Biterm Topic Model.
Modeling Users' Preferences and Social Links in Social Networking Services: A Joint-Evolving Perspective.
Unfolding Temporal Dynamics: Predicting Social Media Popularity Using Multi-scale Temporal Decomposition.
Semantic Community Identification in Large Attribute Networks.
Column-Oriented Datalog Materialization for Large Knowledge Graphs.
Recommendation with Social Dimensions.
Commonsense in Parts: Mining Part-Whole Relations from the Web and Image Tags.
Supervised Hashing via Uncorrelated Component Analysis.
On the Effectiveness of Linear Models for One-Class Collaborative Filtering.
ClaimEval: Integrated and Flexible Framework for Claim Evaluation Using Credibility of Sources.
Context-Sensitive Twitter Sentiment Classification Using Neural Network.
Predicting Online Protest Participation of Social Media Users.
Fortune Teller: Predicting Your Career Path.
Predicting the Next Location: A Recurrent Model with Spatial and Temporal Contexts.
Robust Text Classification in the Presence of Confounding Bias.
Top-N Recommender System via Matrix Completion.
Detect Overlapping Communities via Ranking Node Popularities.
Fusing Social Networks with Deep Learning for Volunteerism Tendency Prediction.
A Scalable Framework to Choose Sellers in E-Marketplaces Using POMDPs.
Improved Neural Machine Translation with SMT Features.
VBPR: Visual Bayesian Personalized Ranking from Implicit Feedback.
Inferring a Personalized Next Point-of-Interest Recommendation Model with Latent Behavior Patterns.
College Towns, Vacation Spots, and Tech Hubs: Using Geo-Social Media to Model and Compare Locations.
Community-Based Question Answering via Heterogeneous Social Network Learning.
Identifying Sentiment Words Using an Optimization Model with L1 Regularization.
Capturing Semantic Correlation for Item Recommendation in Tagging Systems.
Business-Aware Visual Concept Discovery from Social Media for Multimodal Business Venue Recognition.
"8 Amazing Secrets for Getting More Clicks": Detecting Clickbaits in News Streams Using Article Informality.
From Tweets to Wellness: Wellness Event Detection from Twitter Streams.
On the Minimum Differentially Resolving Set Problem for Diffusion Source Inference in Networks.
Survival Prediction by an Integrated Learning Criterion on Intermittently Varying Healthcare Data.
Social Role-Aware Emotion Contagion in Image Social Networks.
Face Behind Makeup.
Learning to Generate Posters of Scientific Papers.
Predicting ICU Mortality Risk by Grouping Temporal Trends from a Multivariate Panel of Physiologic Measurements.
Hospital Stockpiling Problems with Inventory Sharing.
MUST-CNN: A Multilayer Shift-and-Stitch Deep Convolutional Architecture for Sequence-Based Protein Structure Prediction.
Scientific Ranking over Heterogeneous Academic Hypernetwork.
Little Is Much: Bridging Cross-Platform Behaviors through Overlapped Crowds.
Inferring Multi-Dimensional Ideal Points for US Supreme Court Justices.
