aaai 2019 论文列表
The Thirty-Third AAAI Conference on Artificial Intelligence, AAAI 2019, The Thirty-First Innovative Applications of Artificial Intelligence Conference, IAAI 2019, The Ninth AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019, Honolulu, Hawaii, USA, January 27 - February 1, 2019.
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Classifier-Agnostic Saliency Map Extraction.
Adaptation Strategies for Applying AWGN-Based Denoiser to Realistic Noise.
Semi-Supervised Feature Selection with Adaptive Discriminant Analysis.
Geometric Multi-Model Fitting by Deep Reinforcement Learning.
Computing Argumentative Explanations in Bipolar Argumentation Frameworks.
Adversarial Framing for Image and Video Classification.
Sequence to Sequence Learning for Query Expansion.
APRP: An Anonymous Propagation Method in Bitcoin Network.
Manifold Distance-Based Over-Sampling Technique for Class Imbalance Learning.
Towards Gene Function Prediction via Multi-Networks Representation Learning.
Incorporating Context-Relevant Knowledge into Convolutional Neural Networks for Short Text Classification.
DSINE: Deep Structural Influence Learning via Network Embedding.
Improving Full-Body Pose Estimation from a Small Sensor Set Using Artificial Neural Networks and a Kalman Filter.
Heterogeneous Attributed Network Embedding with Graph Convolutional Networks.
Transductive Zero-Shot Learning via Visual Center Adaptation.
Dynamically Identifying Deep Multimodal Features for Image Privacy Prediction.
Robust Facial Landmark Localization Based on Two-Stage Cascaded Pose Regression.
MaMiC: Macro and Micro Curriculum for Robotic Reinforcement Learning.
Binary Classifier Inspired by Quantum Theory.
An Optimal Rewiring Strategy for Cooperative Multiagent Social Learning.
Semi-Supervised Learning for Electron Microscopy Image Segmentation.
Parameterized Heuristics for Incomplete Weighted CSPs.
Symmetrization for Embedding Directed Graphs.
An Adaptive Framework for Conversational Question Answering.
Identifying Bottlenecks in Practical SAT-Based Model Finding for First-Order Logic Ontologies with Datasets.
Towards Sequence-to-Sequence Reinforcement Learning for Constraint Solving with Constraint-Based Local Search.
Desiderata for Interpretability: Explaining Decision Tree Predictions with Counterfactuals.
MIGAN: Malware Image Synthesis Using GANs.
Find a Reasonable Ending for Stories: Does Logic Relation Help the Story Cloze Test?
Examining Political Trustworthiness through Text-Based Measures of Ideology.
Towards Task Understanding in Visual Settings.
A Whole New Ball Game: Harvesting Game Data for Player Profiling.
Lipper: Speaker Independent Speech Synthesis Using Multi-View Lipreading.
Implementation of Boolean AND and OR Logic Gates with Biologically Reasonable Time Constants in Spiking Neural Networks.
Hierarchical Deep Feature Learning for Decoding Imagined Speech from EEG.
Towards Better Accuracy and Robustness with Localized Adversarial Training.
Learning to Transfer Relational Representations through Analogy.
Emergency Department Online Patient-Caregiver Scheduling.
EWGAN: Entropy-Based Wasserstein GAN for Imbalanced Learning.
Learning Representations in Model-Free Hierarchical Reinforcement Learning.
Strategic Tasks for Explainable Reinforcement Learning.
A Feasibility Test on Preventing PRMDs Based on Deep Learning.
Regularizing Fully Convolutional Networks for Time Series Classification by Decorrelating Filters.
An Improved Hierarchical Datastructure for Nearest Neighbor Search.
Frontier Search and Plan Reconstruction in Oversubscription Planning.
On the Role of Syntactic Graph Convolutions for Identifying and Classifying Argument Components.
Logic-Based Sequential Decision-Making.
Learning Document Embeddings with Crossword Prediction.
Adaptive Optimization Framework for Control of Multi-Agent Systems.
The Level Weighted Structural Similarity Loss: A Step Away from MSE.
A Multi-Task Learning Framework for Abstractive Text Summarization.
Towards to Reasonable Decision Basis in Automatic Bone X-Ray Image Classification: A Weakly-Supervised Approach.
Ethically Aligned Mobilization of Community Effort to Reposition Shared Bikes.
Jointly Multiple Hash Learning.
Deep Reinforcement Learning via Past-Success Directed Exploration.
Loss-Balanced Task Weighting to Reduce Negative Transfer in Multi-Task Learning.
Location-Based End-to-End Speech Recognition with Multiple Language Models.
Teaching Machines to Extract Main Content for Machine Reading Comprehension.
Meta-Path Augmented Response Generation.
A Fuzzy Set Based Approach for Rating Bias.
Efficient Neutrino Oscillation Parameter Inference with Gaussian Process.
Cross-Domain Recommendation via Coupled Factorization Machines.
Video-Based Sentiment Analysis with hvnLBP-TOP Feature and bi-LSTM.
Comparing Sample-Wise Learnability across Deep Neural Network Models.
SAX Breakpoints for Random Forest Based Real-Time Contrast Control Chart.
Variational BEJG Solvers for Marginal-MAP Inference with Accurate Approximation of B-Conditional Entropy.
Learning Options with Interest Functions.
A Dynamic Bayesian Network Based Merge Mechanism for Autonomous Vehicles.
Mind Your Language: Abuse and Offense Detection for Code-Switched Languages.
Dynamic Vehicle Traffic Control Using Deep Reinforcement Learning in Automated Material Handling System.
AVS-Net: Automatic Visual Surveillance Using Relation Network.
Higher-Order Multi-Layer Community Detection.
WSD-GAN: Word Sense Disambiguation Using Generative Adversarial Networks.
What's Most Broken? A Tool to Assist Data-Driven Iterative Improvement of an Intelligent Tutoring System.
Reinforcement Learning under Threats.
A Meta-Learning Approach for Custom Model Training.
A Multi-Task Learning Approach for Answer Selection: A Study and a Chinese Law Dataset.
CSEye: A Proposed Solution for Accurate and Accessible One-to-Many Face Verification.
Type Sequence Preserving Heterogeneous Information Network Embedding.
T-Center: A Novel Discriminative Feature Extraction Approach for Iris Recognition.
WAIS: Word Attention for Joint Intent Detection and Slot Filling.
Robust Principal Component Analysis-Based Infrared Small Target Detection.
An Imperfect Algorithm for Coalition Structure Generation.
Matroid Constrained Fair Allocation Problem.
Building Human-Machine Trust via Interpretability.
Partners in Crime: Manipulating the Deferred Acceptance Algorithm through an Accomplice.
An SVM-Based Framework for Long-Term Learning Systems.
Learning Flexible Latent Representations via Encapsulated Variational Encoders.
Identifying Android Malware Using Network-Based Approaches.
CommNets: Communicating Neural Network Architectures for Resource Constrained Systems.
Attention Guided Imitation Learning and Reinforcement Learning.
Stochastic Goal Recognition Design.
Verifiable and Interpretable Reinforcement Learning through Program Synthesis.
Imitation Learning from Observation.
Parameterized Heuristics for Incomplete Weighted CSPs.
Adaptive Modeling for Risk-Aware Decision Making.
Numerical Optimization to AI, and Back.
Multi-View Learning from Disparate Sources for Poverty Mapping.
Learning Generalized Temporal Abstractions across Both Action and Perception.
Using Automated Agents to Teach Negotiation.
Counterfactual Reasoning in Observational Studies.
Reinforcement Learning for Improved Low Resource Dialogue Generation.
Expressive Real-Time Intersection Scheduling.
Adaptive Planning with Evidence Based Prediction for Improved Fluency in Routine Human-Robot Collaborative Tasks.
Multi-Agent Coordination under Uncertain Communication.
A Theory of State Abstraction for Reinforcement Learning.
K3S: Knowledge-Driven Solution Support System.
Temporal Video Analyzer (TVAN): Efficient Temporal Video Analysis for Robust Video Description and Search.
DBA: Dynamic Multi-Armed Bandit Algorithm.
Demo: Learning to Perceive Long-Range Obstacles Using Self-Supervision from Short-Range Sensors.
Realtime Generation of Audible Textures Inspired by a Video Stream.
Global Remote Operation of Intelligent Space Robot Assistants.
QADiver: Interactive Framework for Diagnosing QA Models.
Scientific Article Search System Based on Discourse Facet Representation.
A General Planning-Based Framework for Goal-Driven Conversation Assistant.
Academic Reader: An Interactive Question Answering System on Academic Literatures.
FRIDAYS: A Financial Risk Information Detecting and Analyzing System.
NeuroX: A Toolkit for Analyzing Individual Neurons in Neural Networks.
MAi: An Intelligent Model Acquisition Interface for Interactive Specification of Dialogue Agents.
Proppy: A System to Unmask Propaganda in Online News.
The Rensselaer Mandarin Project - A Cognitive and Immersive Language Learning Environment.
Machine Learning with Crowdsourcing: A Brief Summary of the Past Research and Future Directions.
Borda Count in Collective Decision Making: A Summary of Recent Results.
Is Everything Going According to Plan? Expectations in Goal Reasoning Agents.
Abstractive Summarization: A Survey of the State of the Art.
Performance Evaluation in Machine Learning: The Good, the Bad, the Ugly, and the Way Forward.
Learning and the Unknown: Surveying Steps toward Open World Recognition.
Envisioning AI for K-12: What Should Every Child Know about AI?
Recommender Systems: A Healthy Obsession.
Building Ethically Bounded AI.
Meaningful Explanations of Black Box AI Decision Systems.
Explainable, Normative, and Justified Agency.
Labor Division with Movable Walls: Composing Executable Specifications with Machine Learning and Search (Blue Sky Idea).
Relating the Structure of a Problem and Its Explanation.
Towards Fluid Machine Intelligence: Can We Make a Gifted AI?
Designing Preferences, Beliefs, and Identities for Artificial Intelligence.
Model AI Assignments 2019.
Predicting Unsolvable Deals in the Birds of a Feather Solitaire Game.
Artificial Intelligence Competencies for Data Science Undergraduate Curricula.
A Preliminary Report of Integrating Science and Computing Teaching Using Logic Programming.
PopBots: Designing an Artificial Intelligence Curriculum for Early Childhood Education.
Automating Analysis and Feedback to Improve Mathematics Teachers' Classroom Discourse.
Automatic Generation of Leveled Visual Assessments for Young Learners.
A Neural Network Approach for Birds of a Feather Solvability Prediction.
A Monte Carlo Tree Search Player for Birds of a Feather Solitaire.
Computer Generation of Birds of a Feather Puzzles.
Efficient Solving of Birds of a Feather Puzzles.
Concept Extraction and Prerequisite Relation Learning from Educational Data.
An Integrative Framework for Artificial Intelligence Education.
Get IT Scored Using AutoSAS - An Automated System for Scoring Short Answers.
Machine Learning Based Heuristic Search Algorithms to Solve Birds of a Feather Card Game.
Computational Intractability and Solvability for the Birds of a Feather Game.
A Lightweight Approach to Academic Research Group Management Using Online Tools: Spend More Time on Research and Less on Management.
From Lab to Internship and Back Again: Learning Autonomous Systems through Creating a Research and Development Ecosystem.
Determining Solvability in the Birds of a Feather Card Game.
eRevise: Using Natural Language Processing to Provide Formative Feedback on Text Evidence Usage in Student Writing.
Early Detection of Vacant Parking Spaces Using Dashcam Videos.
DEFSI: Deep Learning Based Epidemic Forecasting with Synthetic Information.
Cleaning Noisy and Heterogeneous Metadata for Record Linking across Scholarly Big Datasets.
Forecasting Intra-Hour Imbalances in Electric Power Systems.
Inferring Concept Prerequisite Relations from Online Educational Resources.
Enhancing Evolutionary Conversion Rate Optimization via Multi-Armed Bandit Algorithms.
Discovering Temporal Patterns from Insurance Interaction Data.
Separating Wheat from Chaff: Joining Biomedical Knowledge and Patient Data for Repurposing Medications.
Artificial Counselor System for Stock Investment.
Identifying Semantics in Clinical Reports Using Neural Machine Translation.
Tagging Address Queries in Maps Search.
Amsterdam to Dublin Eventually Delayed? LSTM and Transfer Learning for Predicting Delays of Low Cost Airlines.
Context-Tree Recommendation vs Matrix-Factorization: Algorithm Selection and Live Users Evaluation.
Bootstrapping Conversational Agents with Weak Supervision.
Ensemble Machine Learning for Estimating Fetal Weight at Varying Gestational Age.
Building Trust in Deep Learning System towards Automated Disease Detection.
Feature Isolation for Hypothesis Testing in Retinal Imaging: An Ischemic Stroke Prediction Case Study.
Profiles, Proxies, and Assumptions: Decentralized, Communications-Resilient Planning, Allocation, and Scheduling.
VPDS: An AI-Based Automated Vehicle Occupancy and Violation Detection System.
Robust Multi-Object Detection Based on Data Augmentation with Realistic Image Synthesis for Point-of-Sale Automation.
Novelty Detection for Multispectral Images with Application to Planetary Exploration.
Leveraging Textual Specifications for Grammar-Based Fuzzing of Network Protocols.
A Machine Learning Suite for Machine Components' Health-Monitoring.
Logistic Regression on Homomorphic Encrypted Data at Scale.
Automatic Generation of Chinese Short Product Titles for Mobile Display.
Satellite Detection of Moving Vessels in Marine Environments.
DeBGUer: A Tool for Bug Prediction and Diagnosis.
Expert Guided Rule Based Prioritization of Scientifically Relevant Images for Downlinking over Limited Bandwidth from Planetary Orbiters.
A Fast Machine Learning Workflow for Rapid Phenotype Prediction from Whole Shotgun Metagenomes.
Anomaly Detection Using Autoencoders in High Performance Computing Systems.
Probabilistic-Logic Bots for Efficient Evaluation of Business Rules Using Conversational Interfaces.
Querying NoSQL with Deep Learning to Answer Natural Language Questions.
Early-Stopping of Scattering Pattern Observation with Bayesian Modeling.
Linking Educational Resources on Data Science.
Remote Management of Boundary Protection Devices with Information Restrictions.
Grading Uncompilable Programs.
Automated Dispatch of Helpdesk Email Tickets: Pushing the Limits with AI.
Transforming Underwriting in the Life Insurance Industry.
Large Scale Personalized Categorization of Financial Transactions.
A Genetic Algorithm for Finding a Small and Diverse Set of Recent News Stories on a Given Subject: How We Generate AAAI's AI-Alert.
Calibrated Stochastic Gradient Descent for Convolutional Neural Networks.
Deep Embedding Features for Salient Object Detection.
Singe Image Rain Removal with Unpaired Information: A Differentiable Programming Perspective.
Dynamic Capsule Attention for Visual Question Answering.
Free VQA Models from Knowledge Inertia by Pairwise Inconformity Learning.
A Robust and Efficient Algorithm for the PnL Problem Using Algebraic Distance to Approximate the Reprojection Distance.
Talking Face Generation by Adversarially Disentangled Audio-Visual Representation.
Towards Optimal Fine Grained Retrieval via Decorrelated Centralized Loss with Normalize-Scale Layer.
Learning Fully Dense Neural Networks for Image Semantic Segmentation.
Recurrent Attention Model for Pedestrian Attribute Recognition.
3D Object Detection Using Scale Invariant and Feature Reweighting Networks.
M2Det: A Single-Shot Object Detector Based on Multi-Level Feature Pyramid Network.
Look across Elapse: Disentangled Representation Learning and Photorealistic Cross-Age Face Synthesis for Age-Invariant Face Recognition.
Learning Incremental Triplet Margin for Person Re-Identification.
Learning a Key-Value Memory Co-Attention Matching Network for Person Re-Identification.
Learning Transferable Self-Attentive Representations for Action Recognition in Untrimmed Videos with Weak Supervision.
Learning to Localize Objects with Noisy Labeled Instances.
Understanding Pictograph with Facial Features: End-to-End Sentence-Level Lip Reading of Chinese.
Cousin Network Guided Sketch Recognition via Latent Attribute Warehouse.
Multi-Attribute Transfer via Disentangled Representation.
Large-Scale Visual Relationship Understanding.
ACM: Adaptive Cross-Modal Graph Convolutional Neural Networks for RGB-D Scene Recognition.
Memory-Augmented Temporal Dynamic Learning for Action Recognition.
To Find Where You Talk: Temporal Sentence Localization in Video with Attention Based Location Regression.
Tensor Ring Decomposition with Rank Minimization on Latent Space: An Efficient Approach for Tensor Completion.
Cycle-SUM: Cycle-Consistent Adversarial LSTM Networks for Unsupervised Video Summarization.
Spatial Mixture Models with Learnable Deep Priors for Perceptual Grouping.
ActivityNet-QA: A Dataset for Understanding Complex Web Videos via Question Answering.
PVRNet: Point-View Relation Neural Network for 3D Shape Recognition.
Instance-Level Facial Attributes Transfer with Geometry-Aware Flow.
Safeguarded Dynamic Label Regression for Noisy Supervision.
Learning a Visual Tracker from a Single Movie without Annotation.
Efficient Image Retrieval via Decoupling Diffusion into Online and Offline Processing.
A Dual Attention Network with Semantic Embedding for Few-Shot Learning.
Segregated Temporal Assembly Recurrent Networks for Weakly Supervised Multiple Action Detection.
Multilevel Language and Vision Integration for Text-to-Clip Retrieval.
Residual Attribute Attention Network for Face Image Super-Resolution.
DeRPN: Taking a Further Step toward More General Object Detection.
Scene Text Detection with Supervised Pyramid Context Network.
Semantic Adversarial Network with Multi-Scale Pyramid Attention for Video Classification.
What and Where the Themes Dominate in Image.
Multiple Saliency and Channel Sensitivity Network for Aggregated Convolutional Feature.
Disentangled Variational Representation for Heterogeneous Face Recognition.
Differential Networks for Visual Question Answering.
Graph CNNs with Motif and Variable Temporal Block for Skeleton-Based Action Recognition.
Learning Non-Uniform Hypergraph for Multi-Object Tracking.
Sparse Adversarial Perturbations for Videos.
Learning to Compose Topic-Aware Mixture of Experts for Zero-Shot Video Captioning.
Hierarchical Attention Network for Image Captioning.
MVPNet: Multi-View Point Regression Networks for 3D Object Reconstruction from A Single Image.
Deep Single-View 3D Object Reconstruction with Visual Hull Embedding.
Spatial-Temporal Person Re-Identification.
Learning Basis Representation to Refine 3D Human Pose Estimations.
Robust Deep Co-Saliency Detection with Group Semantic.
Hierarchical Photo-Scene Encoder for Album Storytelling.
A Layer-Based Sequential Framework for Scene Generation with GANs.
Towards Highly Accurate and Stable Face Alignment for High-Resolution Videos.
Connecting Language to Images: A Progressive Attention-Guided Network for Simultaneous Image Captioning and Language Grounding.
KVQA: Knowledge-Aware Visual Question Answering.
Almost Unsupervised Learning for Dense Crowd Counting.
Backbone Cannot Be Trained at Once: Rolling Back to Pre-Trained Network for Person Re-Identification.
MonoGRNet: A Geometric Reasoning Network for Monocular 3D Object Localization.
Weakly Supervised Scene Parsing with Point-Based Distance Metric Learning.
Learning Attribute-Specific Representations for Visual Tracking.
Dual Semi-Supervised Learning for Facial Action Unit Recognition.
CAPNet: Continuous Approximation Projection for 3D Point Cloud Reconstruction Using 2D Supervision.
Recognizing Unseen Attribute-Object Pair with Generative Model.
Detect or Track: Towards Cost-Effective Video Object Detection/Tracking.
Deep Video Frame Interpolation Using Cyclic Frame Generation.
Spatial and Temporal Mutual Promotion for Video-Based Person Re-Identification.
Point2Sequence: Learning the Shape Representation of 3D Point Clouds with an Attention-Based Sequence to Sequence Network.
DDFlow: Learning Optical Flow with Unlabeled Data Distillation.
Joint Dynamic Pose Image and Space Time Reversal for Human Action Recognition from Videos.
Optimal Projection Guided Transfer Hashing for Image Retrieval.
Learning Neural Bag-of-Matrix-Summarization with Riemannian Network.
A Bottom-Up Clustering Approach to Unsupervised Person Re-Identification.
Hypergraph Optimization for Multi-Structural Geometric Model Fitting.
Towards Optimal Discrete Online Hashing with Balanced Similarity.
Scene Text Recognition from Two-Dimensional Perspective.
Unsupervised Cross-Spectral Stereo Matching by Learning to Synthesize.
PCGAN: Partition-Controlled Human Image Generation.
Zero-Shot Object Detection with Textual Descriptions.
Angular Triplet-Center Loss for Multi-View 3D Shape Retrieval.
Temporal Bilinear Networks for Video Action Recognition.
Robust Estimation of Similarity Transformation for Visual Object Tracking.
Beyond RNNs: Positional Self-Attention with Co-Attention for Video Question Answering.
Learning Object Context for Dense Captioning.
Distribution Consistency Based Covariance Metric Networks for Few-Shot Learning.
Visual-Semantic Graph Reasoning for Pedestrian Attribute Recognition.
Meta Learning for Image Captioning.
Multi-Scale 3D Convolution Network for Video Based Person Re-Identification.
Show, Attend and Read: A Simple and Strong Baseline for Irregular Text Recognition.
Heterogeneous Transfer Learning via Deep Matrix Completion with Adversarial Kernel Embedding.
Semantic Relationships Guided Representation Learning for Facial Action Unit Recognition.
Skeleton-Based Gesture Recognition Using Several Fully Connected Layers with Path Signature Features and Temporal Transformer Module.
Gradient Harmonized Single-Stage Detector.
SuperVAE: Superpixelwise Variational Autoencoder for Salient Object Detection.
Spatio-Temporal Graph Routing for Skeleton-Based Action Recognition.
BiHMP-GAN: Bidirectional 3D Human Motion Prediction GAN.
Self-Supervised Video Representation Learning with Space-Time Cubic Puzzles.
Discriminative Feature Learning for Unsupervised Video Summarization.
Video Object Detection with Locally-Weighted Deformable Neighbors.
Image Saliency Prediction in Transformed Domain: A Deep Complex Neural Network Method.
MLVCNN: Multi-Loop-View Convolutional Neural Network for 3D Shape Retrieval.
DeepCCFV: Camera Constraint-Free Multi-View Convolutional Neural Network for 3D Object Retrieval.
Attentive Temporal Pyramid Network for Dynamic Scene Classification.
Few-Shot Image and Sentence Matching via Gated Visual-Semantic Embedding.
3D Volumetric Modeling with Introspective Neural Networks.
A Framework to Coordinate Segmentation and Recognition.
Hierarchically Structured Reinforcement Learning for Topically Coherent Visual Story Generation.
Re2EMA: Regularized and Reinitialized Exponential Moving Average for Target Model Update in Object Tracking.
A Novel Framework for Robustness Analysis of Visual QA Models.
Attention-Based Multi-Context Guiding for Few-Shot Semantic Segmentation.
Learning to Steer by Mimicking Features from Heterogeneous Auxiliary Networks.
Weighted Channel Dropout for Regularization of Deep Convolutional Neural Network.
Non-Local Context Encoder: Robust Biomedical Image Segmentation against Adversarial Attacks.
Mono3D++: Monocular 3D Vehicle Detection with Two-Scale 3D Hypotheses and Task Priors.
StNet: Local and Global Spatial-Temporal Modeling for Action Recognition.
Read, Watch, and Move: Reinforcement Learning for Temporally Grounding Natural Language Descriptions in Videos.
HSME: Hypersphere Manifold Embedding for Visible Thermal Person Re-Identification.
View Inter-Prediction GAN: Unsupervised Representation Learning for 3D Shapes by Learning Global Shape Memories to Support Local View Predictions.
Depthwise Convolution Is All You Need for Learning Multiple Visual Domains.
Dual-View Ranking with Hardness Assessment for Zero-Shot Learning.
Human Action Transfer Based on 3D Model Reconstruction.
Projection Convolutional Neural Networks for 1-bit CNNs via Discrete Back Propagation.
No-Reference Image Quality Assessment with Reinforcement Recursive List-Wise Ranking.
Video Imprint Segmentation for Temporal Action Detection in Untrimmed Videos.
Deliberate Attention Networks for Image Captioning.
Perceptual Pyramid Adversarial Networks for Text-to-Image Synthesis.
I Know the Relationships: Zero-Shot Action Recognition via Two-Stream Graph Convolutional Networks and Knowledge Graphs.
Horizontal Pyramid Matching for Person Re-Identification.
STA: Spatial-Temporal Attention for Large-Scale Video-Based Person Re-Identification.
MeshNet: Mesh Neural Network for 3D Shape Representation.
Fully Convolutional Video Captioning with Coarse-to-Fine and Inherited Attention.
Cubic LSTMs for Video Prediction.
Learning a Deep Convolutional Network for Colorization in Monochrome-Color Dual-Lens System.
Attention-Aware Sampling via Deep Reinforcement Learning for Action Recognition.
Residual Compensation Networks for Heterogeneous Face Recognition.
Selective Refinement Network for High Performance Face Detection.
Data Fine-Tuning.
Learning Resolution-Invariant Deep Representations for Person Re-Identification.
Unsupervised Bilingual Lexicon Induction from Mono-Lingual Multimodal Data.
Semantic Proposal for Activity Localization in Videos via Sentence Query.
Motion Guided Spatial Attention for Video Captioning.
Similarity Preserving Deep Asymmetric Quantization for Image Retrieval.
Localizing Natural Language in Videos.
Temporal Deformable Convolutional Encoder-Decoder Networks for Video Captioning.
Unsupervised Meta-Learning of Figure-Ground Segmentation via Imitating Visual Effects.
Unsupervised Stylish Image Description Generation via Domain Layer Norm.
Improving Image Captioning with Conditional Generative Adversarial Nets.
Energy Confused Adversarial Metric Learning for Zero-Shot Image Retrieval and Clustering.
GaitSet: Regarding Gait as a Set for Cross-View Gait Recognition.
Action Knowledge Transfer for Action Prediction with Partial Videos.
MR-NET: Exploiting Mutual Relation for Visual Relationship Detection.
BLOCK: Bilinear Superdiagonal Fusion for Visual Question Answering and Visual Relationship Detection.
Object Detection Based on Region Decomposition and Assembly.
Densely Supervised Grasp Detector (DSGD).
TallyQA: Answering Complex Counting Questions.
Probabilistic Model Checking of Robots Deployed in Extreme Environments.
That's Mine! Learning Ownership Relations and Norms for Robots.
Personalized Robot Tutoring Using the Assistive Tutor POMDP (AT-POMDP).
Deictic Image Mapping: An Abstraction for Learning Pose Invariant Manipulation Policies.
Visual Place Recognition via Robust ℓ2-Norm Distance Based Holism and Landmark Integration.
Mirroring without Overimitation: Learning Functionally Equivalent Manipulation Actions.
Adversarial Actor-Critic Method for Task and Motion Planning Problems Using Planning Experience.
MotionTransformer: Transferring Neural Inertial Tracking between Domains.
Depth Prediction without the Sensors: Leveraging Structure for Unsupervised Learning from Monocular Videos.
Optimizing Discount and Reputation Trade-Offs in E-Commerce Systems: Characterization and Online Learning.
Counting and Sampling Markov Equivalent Directed Acyclic Graphs.
Lifted Hinge-Loss Markov Random Fields.
Compiling Bayesian Network Classifiers into Decision Graphs.
Structured Bayesian Networks: From Inference to Learning with Routes.
Rethinking the Discount Factor in Reinforcement Learning: A Decision Theoretic Approach.
Memory Bounded Open-Loop Planning in Large POMDPs Using Thompson Sampling.
Semi-Parametric Sampling for Stochastic Bandits with Many Arms.
Anytime Recursive Best-First Search for Bounding Marginal MAP.
On Lifted Inference Using Neural Embeddings.
Robust Ordinal Embedding from Contaminated Relative Comparisons.
Interleave Variational Optimization with Monte Carlo Sampling: A Tale of Two Approximate Inference Paradigms.
Finding All Bayesian Network Structures within a Factor of Optimal.
Dirichlet Multinomial Mixture with Variational Manifold Regularization: Topic Modeling over Short Texts.
Randomized Strategies for Robust Combinatorial Optimization.
Polynomial-Time Probabilistic Reasoning with Partial Observations via Implicit Learning in Probability Logics.
MFBO-SSM: Multi-Fidelity Bayesian Optimization for Fast Inference in State-Space Models.
Collective Online Learning of Gaussian Processes in Massive Multi-Agent Systems.
A Generative Model for Dynamic Networks with Applications.
Marginal Inference in Continuous Markov Random Fields Using Mixtures.
Exact and Approximate Weighted Model Integration with Probability Density Functions Using Knowledge Compilation.
Fast Relational Probabilistic Inference and Learning: Approximate Counting via Hypergraphs.
Efficient Optimal Approximation of Discrete Random Variables for Estimation of Probabilities of Missing Deadlines.
Path-Specific Counterfactual Fairness.
Learning Diverse Bayesian Networks.
On the Hardness of Probabilistic Inference Relaxations.
On Testing of Uniform Samplers.
Probabilistic Logic Programming with Beta-Distributed Random Variables.
Robustness Guarantees for Bayesian Inference with Gaussian Processes.
Machine Teaching for Inverse Reinforcement Learning: Algorithms and Applications.
Active Preference Learning Based on Generalized Gini Functions: Application to the Multiagent Knapsack Problem.
Online Multi-Agent Pathfinding.
Rotational Diversity in Multi-Cycle Assignment Problems.
Deep Learning for Cost-Optimal Planning: Task-Dependent Planner Selection.
An Innovative Genetic Algorithm for the Quantum Circuit Compilation Problem.
Distribution-Based Semi-Supervised Learning for Activity Recognition.
Acting and Planning Using Operational Models.
Automated Verification of Social Laws for Continuous Time Multi-Robot Systems.
Temporal Planning with Temporal Metric Trajectory Constraints.
Sliding Window Temporal Graph Coloring.
Performance Guarantees for Homomorphisms beyond Markov Decision Processes.
Lifelong Path Planning with Kinematic Constraints for Multi-Agent Pickup and Delivery.
Searching with Consistent Prioritization for Multi-Agent Path Finding.
Moral Permissibility of Action Plans.
Multi-Agent Path Finding for Large Agents.
Red-Black Heuristics for Planning Tasks with Conditional Effects.
Generalized Planning via Abstraction: Arbitrary Numbers of Objects.
Learning How to Ground a Plan - Partial Grounding in Classical Planning.
Solving Multiagent Planning Problems with Concurrent Conditional Effects.
Operator Mutexes and Symmetries for Simplifying Planning Tasks.
Refining Abstraction Heuristics during Real-Time Planning.
Learning Resource Allocation and Pricing for Cloud Profit Maximization.
Efficiently Reasoning with Interval Constraints in Forward Search Planning.
Efficient Temporal Planning Using Metastates.
Improving Domain-Independent Planning via Critical Section Macro-Operators.
Robustness Envelopes for Temporal Plans.
Deep Reactive Policies for Planning in Stochastic Nonlinear Domains.
Bringing Order to Chaos - A Compact Representation of Partial Order in SAT-Based HTN Planning.
Measurement Maximizing Adaptive Sampling with Risk Bounding Functions.
Plan-Length Bounds: Beyond 1-Way Dependency.
An Affect-Rich Neural Conversational Model with Biased Attention and Weighted Cross-Entropy Loss.
Multi-Labeled Relation Extraction with Attentive Capsule Network.
Generating Character Descriptions for Automatic Summarization of Fiction.
A Neural Network Approach to Verb Phrase Ellipsis Resolution.
Generating Chinese Ci with Designated Metrical Structure.
A Generalized Language Model in Tensor Space.
DRr-Net: Dynamic Re-Read Network for Sentence Semantic Matching.
Bidirectional Transition-Based Dependency Parsing.
Exploring Answer Stance Detection with Recurrent Conditional Attention.
Distant Supervision for Relation Extraction with Linear Attenuation Simulation and Non-IID Relevance Embedding.
Combining Axiom Injection and Knowledge Base Completion for Efficient Natural Language Inference.
Data Augmentation for Spoken Language Understanding via Joint Variational Generation.
TopicEq: A Joint Topic and Mathematical Equation Model for Scientific Texts.
ScisummNet: A Large Annotated Corpus and Content-Impact Models for Scientific Paper Summarization with Citation Networks.
Plan-and-Write: Towards Better Automatic Storytelling.
Graph Convolutional Networks for Text Classification.
Exploring Human-Like Reading Strategy for Abstractive Text Summarization.
A Deep Cascade Model for Multi-Document Reading Comprehension.
End-to-End Knowledge-Routed Relational Dialogue System for Automatic Diagnosis.
Modeling Coherence for Discourse Neural Machine Translation.
Distributed Representation of Words in Cause and Effect Spaces.
Quantifying Uncertainties in Natural Language Processing Tasks.
Adaptive Region Embedding for Text Classification.
Syntax-Aware Neural Semantic Role Labeling.
Graph Based Translation Memory for Neural Machine Translation.
Switch-Based Active Deep Dyna-Q: Efficient Adaptive Planning for Task-Completion Dialogue Policy Learning.
Response Generation by Context-Aware Prototype Editing.
Improving Distantly Supervised Relation Extraction with Neural Noise Converter and Conditional Optimal Selector.
Reverse-Engineering Satire, or "Paper on Computational Humor Accepted despite Making Serious Advances".
Translating with Bilingual Topic Knowledge for Neural Machine Translation.
A Topic-Aware Reinforced Model for Weakly Supervised Stance Detection.
Better Fine-Tuning via Instance Weighting for Text Classification.
When Do Words Matter? Understanding the Impact of Lexical Choice on Audience Perception Using Individual Treatment Effect Estimation.
A Deep Reinforcement Learning Based Multi-Step Coarse to Fine Question Answering (MSCQA) System.
Words Can Shift: Dynamically Adjusting Word Representations Using Nonverbal Behaviors.
Improving Natural Language Inference Using External Knowledge in the Science Questions Domain.
Unsupervised Learning Helps Supervised Neural Word Segmentation.
Transferable Interactive Memory Network for Domain Adaptation in Fine-Grained Opinion Extraction.
Hierarchical Attention Networks for Sentence Ordering.
A Task in a Suit and a Tie: Paraphrase Generation with Semantic Augmentation.
A Multi-Agent Communication Framework for Question-Worthy Phrase Extraction and Question Generation.
Chinese NER with Height-Limited Constituent Parsing.
Logic Attention Based Neighborhood Aggregation for Inductive Knowledge Graph Embedding.
Template-Based Math Word Problem Solvers with Recursive Neural Networks.
What if We Simply Swap the Two Text Fragments? A Straightforward yet Effective Way to Test the Robustness of Methods to Confounding Signals in Nature Language Inference Tasks.
Improving Hypernymy Prediction via Taxonomy Enhanced Adversarial Learning.
A Natural Language Corpus of Common Grounding under Continuous and Partially-Observable Context.
CompareLDA: A Topic Model for Document Comparison.
Near-Lossless Binarization of Word Embeddings.
Generating Live Soccer-Match Commentary from Play Data.
Multi-Matching Network for Multiple Choice Reading Comprehension.
Jointly Extracting Multiple Triplets with Multilayer Translation Constraints.
A Hierarchical Framework for Relation Extraction with Reinforcement Learning.
QUAREL: A Dataset and Models for Answering Questions about Qualitative Relationships.
A Grammar-Based Structural CNN Decoder for Code Generation.
Towards Sentence-Level Brain Decoding with Distributed Representations.
Distantly Supervised Entity Relation Extraction with Adapted Manual Annotations.
Fast PMI-Based Word Embedding with Efficient Use of Unobserved Patterns.
Exploring Knowledge Graphs in an Interpretable Composite Approach for Text Entailment.
GlobalTrait: Personality Alignment of Multilingual Word Embeddings.
A Deep Sequential Model for Discourse Parsing on Multi-Party Dialogues.
DeepChannel: Salience Estimation by Contrastive Learning for Extractive Document Summarization.
Learning to Embed Sentences Using Attentive Recursive Trees.
Analysis of Joint Multilingual Sentence Representations and Semantic K-Nearest Neighbor Graphs.
Challenges in the Automatic Analysis of Students' Diagnostic Reasoning.
Learning Semantic Representations for Novel Words: Leveraging Both Form and Context.
On Resolving Ambiguous Anaphoric Expressions in Imperative Discourse.
A Hierarchical Multi-Task Approach for Learning Embeddings from Semantic Tasks.
Revisiting LSTM Networks for Semi-Supervised Text Classification via Mixed Objective Function.
COALA: A Neural Coverage-Based Approach for Long Answer Selection with Small Data.
Zero-Shot Neural Transfer for Cross-Lingual Entity Linking.
Jointly Learning to Label Sentences and Tokens.
Data-to-Text Generation with Content Selection and Planning.
Unseen Word Representation by Aligning Heterogeneous Lexical Semantic Spaces.
Found in Translation: Learning Robust Joint Representations by Cyclic Translations between Modalities.
Paraphrase Diversification Using Counterfactual Debiasing.
HAS-QA: Hierarchical Answer Spans Model for Open-Domain Question Answering.
Analyzing Compositionality-Sensitivity of NLI Models.
Combining Fact Extraction and Verification with Neural Semantic Matching Networks.
One for All: Neural Joint Modeling of Entities and Events.
Spell Once, Summon Anywhere: A Two-Level Open-Vocabulary Language Model.
CGMH: Constrained Sentence Generation by Metropolis-Hastings Sampling.
Weakly-Supervised Hierarchical Text Classification.
DialogueRNN: An Attentive RNN for Emotion Detection in Conversations.
LiveBot: Generating Live Video Comments Based on Visual and Textual Contexts.
SAM-Net: Integrating Event-Level and Chain-Level Attentions to Predict What Happens Next.
Learning Personalized End-to-End Goal-Oriented Dialog.
Hierarchical Encoder with Auxiliary Supervision for Neural Table-to-Text Generation: Learning Better Representation for Tables.
Unsupervised Post-Processing of Word Vectors via Conceptor Negation.
FANDA: A Novel Approach to Perform Follow-Up Query Analysis.
Contextualized Non-Local Neural Networks for Sequence Learning.
Exploiting the Ground-Truth: An Adversarial Imitation Based Knowledge Distillation Approach for Event Detection.
Leveraging Web Semantic Knowledge in Word Representation Learning.
A Generalized Idiom Usage Recognition Model Based on Semantic Compatibility.
Dependency or Span, End-to-End Uniform Semantic Role Labeling.
Dialogue Generation: From Imitation Learning to Inverse Reinforcement Learning.
A Unified Model for Opinion Target Extraction and Target Sentiment Prediction.
Neural Speech Synthesis with Transformer Network.
Insufficient Data Can Also Rock! Learning to Converse Using Smaller Data with Augmentation.
Towards Personalized Review Summarization via User-Aware Sequence Network.
Differentiated Distribution Recovery for Neural Text Generation.
What Should I Learn First: Introducing LectureBank for NLP Education and Prerequisite Chain Learning.
Knowledge-Driven Encode, Retrieve, Paraphrase for Medical Image Report Generation.
Dependency Grammar Induction with a Neural Variational Transition-Based Parser.
A Human-Like Semantic Cognition Network for Aspect-Level Sentiment Classification.
Zero-Shot Adaptive Transfer for Conversational Language Understanding.
Lattice CNNs for Matching Based Chinese Question Answering.
Fast and Simple Mixture of Softmaxes with BPE and Hybrid-LightRNN for Language Generation.
Neural Machine Translation with Adequacy-Oriented Learning.
Domain Agnostic Real-Valued Specificity Prediction.
Improving Neural Question Generation Using Answer Separation.
Dynamic Compositionality in Recursive Neural Networks with Structure-Aware Tag Representations.
Semantic Sentence Matching with Densely-Connected Recurrent and Co-Attentive Information.
Predicting the Argumenthood of English Prepositional Phrases.
Understanding Actors and Evaluating Personae with Gaussian Embeddings.
Word Embedding as Maximum A Posteriori Estimation.
Unsupervised Controllable Text Formalization.
Dictionary-Guided Editing Networks for Paraphrase Generation.
Recurrent Poisson Process Unit for Speech Recognition.
Read + Verify: Machine Reading Comprehension with Unanswerable Questions.
PARABANK: Monolingual Bitext Generation and Sentential Paraphrasing via Lexically-Constrained Neural Machine Translation.
Neural Relation Extraction within and across Sentence Boundaries.
Document Informed Neural Autoregressive Topic Models with Distributional Prior.
GIRNet: Interleaved Multi-Task Recurrent State Sequence Models.
Gaussian Transformer: A Lightweight Approach for Natural Language Inference.
Long Short-Term Memory with Dynamic Skip Connections.
Story Ending Generation with Incremental Encoding and Commonsense Knowledge.
Deep Cascade Multi-Task Learning for Slot Filling in Online Shopping Assistant.
Switch-LSTMs for Multi-Criteria Chinese Word Segmentation.
Sentence-Wise Smooth Regularization for Sequence to Sequence Learning.
MNCN: A Multilingual Ngram-Based Convolutional Network for Aspect Category Detection in Online Reviews.
Kernelized Hashcode Representations for Relation Extraction.
Generating Distractors for Reading Comprehension Questions from Real Examinations.
Predicting and Analyzing Language Specificity in Social Media Posts.
Hybrid Attention-Based Prototypical Networks for Noisy Few-Shot Relation Classification.
Abstractive Text Summarization by Incorporating Reader Comments.
Structured Two-Stream Attention Network for Video Question Answering.
Generating Multiple Diverse Responses for Short-Text Conversation.
EA Reader: Enhance Attentive Reader for Cloze-Style Question Answering via Multi-Space Context Fusion.
"Bilingual Expert" Can Find Translation Errors.
Explicit Interaction Model towards Text Classification.
Adapting Translation Models for Transcript Disfluency Detection.
From Independent Prediction to Reordered Prediction: Integrating Relative Position and Global Label Information to Emotion Cause Identification.
A Pattern-Based Approach to Recognizing Time Expressions.
Training Temporal Word Embeddings with a Compass.
Multi-Task Learning with Multi-View Attention for Answer Selection and Knowledge Base Question Answering.
What Is One Grain of Sand in the Desert? Analyzing Individual Neurons in Deep NLP Models.
Joint Extraction of Entities and Overlapping Relations Using Position-Attentive Sequence Labeling.
Recurrent Stacking of Layers for Compact Neural Machine Translation Models.
Implicit Argument Prediction as Reading Comprehension.
Convolutional Spatial Attention Model for Reading Comprehension with Multiple-Choice Questions.
Title-Guided Encoding for Keyphrase Generation.
Transfer Learning for Sequence Labeling Using Source Model and Target Data.
Deep Short Text Classification with Knowledge Powered Attention.
Incorporating Structured Commonsense Knowledge in Story Completion.
GRN: Gated Relation Network to Enhance Convolutional Neural Network for Named Entity Recognition.
Automated Rule Base Completion as Bayesian Concept Induction.
Re-Evaluating ADEM: A Deeper Look at Scoring Dialogue Responses.
AutoSense Model for Word Sense Induction.
Antonym-Synonym Classification Based on New Sub-Space Embeddings.
Online Embedding Compression for Text Classification Using Low Rank Matrix Factorization.
Enriching Word Embeddings with a Regressor Instead of Labeled Corpora.
Probabilistic Alternating-Time µ-Calculus.
Multiagent Decision Making For Maritime Traffic Management.
Theory of Minds: Understanding Behavior in Groups through Inverse Planning.
Multi-Winner Contests for Strategic Diffusion in Social Networks.
Evolution of Collective Fairness in Hybrid Populations of Humans and Agents.
Overcoming Blind Spots in the Real World: Leveraging Complementary Abilities for Joint Execution.
Learning to Teach in Cooperative Multiagent Reinforcement Learning.
TrafficPredict: Trajectory Prediction for Heterogeneous Traffic-Agents.
Leveraging Observations in Bandits: Between Risks and Benefits.
Large Scale Learning of Agent Rationality in Two-Player Zero-Sum Games.
Multi-Agent Discussion Mechanism for Natural Language Generation.
Symmetry-Breaking Constraints for Grid-Based Multi-Agent Path Finding.
Message-Dropout: An Efficient Training Method for Multi-Agent Deep Reinforcement Learning.
General Robustness Evaluation of Incentive Mechanism against Bounded Rationality Using Continuum-Armed Bandits.
IPOMDP-Net: A Deep Neural Network for Partially Observable Multi-Agent Planning Using Interactive POMDPs.
Successor Features Based Multi-Agent RL for Event-Based Decentralized MDPs.
Distributed Community Detection via Metastability of the 2-Choices Dynamics.
A Generic Approach to Accelerating Belief Propagation Based Incomplete Algorithms for DCOPs via a Branch-and-Bound Technique.
An Abstraction-Based Method for Verifying Strategic Properties in Multi-Agent Systems with Imperfect Information.
Consensus in Opinion Formation Processes in Fully Evolving Environments.
Bayesian Execution Skill Estimation.
Verification of RNN-Based Neural Agent-Environment Systems.
Consensus Adversarial Domain Adaptation.
Aligning Domain-Specific Distribution and Classifier for Cross-Domain Classification from Multiple Sources.
Residual Invertible Spatio-Temporal Network for Video Super-Resolution.
DAN: Deep Attention Neural Network for News Recommendation.
A Domain Generalization Perspective on Listwise Context Modeling.
Communication-Optimal Distributed Dynamic Graph Clustering.
An Efficient Compressive Convolutional Network for Unified Object Detection and Image Compression.
Deep Interest Evolution Network for Click-Through Rate Prediction.
Self-Supervised Mixture-of-Experts by Uncertainty Estimation.
Capacity Control of ReLU Neural Networks by Basis-Path Norm.
Understanding VAEs in Fisher-Shannon Plane.
A New Ensemble Learning Framework for 3D Biomedical Image Segmentation.
Biomedical Image Segmentation via Representative Annotation.
Self-Adversarially Learned Bayesian Sampling.
InfoVAE: Balancing Learning and Inference in Variational Autoencoders.
Where to Go Next: A Spatio-Temporal Gated Network for Next POI Recommendation.
The Adversarial Attack and Detection under the Fisher Information Metric.
Submodular Optimization over Streams with Inhomogeneous Decays.
SADIH: Semantic-Aware DIscrete Hashing.
Learning Uniform Semantic Features for Natural Language and Programming Language Globally, Locally and Sequentially.
Learning (from) Deep Hierarchical Structure among Features.
Bayesian Graph Convolutional Neural Networks for Semi-Supervised Classification.
CAFE: Adaptive VDI Workload Prediction with Multi-Grained Features.
Find Me if You Can: Deep Software Clone Detection by Exploiting the Contest between the Plagiarist and the Detector.
Hashtag Recommendation for Photo Sharing Services.
QUOTA: The Quantile Option Architecture for Reinforcement Learning.
ACE: An Actor Ensemble Algorithm for Continuous Control with Tree Search.
Learning to Communicate and Solve Visual Blocks-World Tasks.
Interactive Attention Transfer Network for Cross-Domain Sentiment Classification.
A Powerful Global Test Statistic for Functional Statistical Inference.
RecurJac: An Efficient Recursive Algorithm for Bounding Jacobian Matrix of Neural Networks and Its Applications.
Learning Set Functions with Limited Complementarity.
Active Mini-Batch Sampling Using Repulsive Point Processes.
Partially Observable Multi-Sensor Sequential Change Detection: A Combinatorial Multi-Armed Bandit Approach.
f-Similarity Preservation Loss for Soft Labels: A Demonstration on Cross-Corpus Speech Emotion Recognition.
Interpreting Deep Models for Text Analysis via Optimization and Regularization Methods.
Multi-Order Attentive Ranking Model for Sequential Recommendation.
Network Recasting: A Universal Method for Network Architecture Transformation.
Parallel Restarted SGD with Faster Convergence and Less Communication: Demystifying Why Model Averaging Works for Deep Learning.
Iterative Classroom Teaching.
Balanced Sparsity for Efficient DNN Inference on GPU.
Revisiting Spatial-Temporal Similarity: A Deep Learning Framework for Traffic Prediction.
Learning Personalized Attribute Preference via Multi-Task AUC Optimization.
Deep Robust Unsupervised Multi-Modal Network.
Unsupervised Fake News Detection on Social Media: A Generative Approach.
Confidence Weighted Multitask Learning.
Training Deep Neural Networks in Generations: A More Tolerant Teacher Educates Better Students.
Weighted Oblique Decision Trees.
Cross-Domain Visual Representations via Unsupervised Graph Alignment.
Oversampling for Imbalanced Data via Optimal Transport.
Frame and Feature-Context Video Super-Resolution.
Active Learning of Multi-Class Classification Models from Ordered Class Sets.
Self-Ensembling Attention Networks: Addressing Domain Shift for Semantic Segmentation.
Task-Driven Common Representation Learning via Bridge Neural Network.
Data-Distortion Guided Self-Distillation for Deep Neural Networks.
Partial Label Learning via Label Enhancement.
Dueling Bandits with Qualitative Feedback.
Embedding-Based Complex Feature Value Coupling Learning for Detecting Outliers in Non-IID Categorical Data.
Hierarchical Classification Based on Label Distribution Learning.
Modeling Local Dependence in Natural Language with Multi-Channel Recurrent Neural Networks.
SpHMC: Spectral Hamiltonian Monte Carlo.
Multi-View Multi-Instance Multi-Label Learning Based on Collaborative Matrix Factorization.
Learning Dynamic Generator Model by Alternating Back-Propagation through Time.
Understanding Persuasion Cascades in Online Product Rating Systems.
RS3CIS: Robust Single-Step Spectral Clustering with Intrinsic Subspace.
Bayesian Deep Collaborative Matrix Factorization.
Tied Transformers: Neural Machine Translation with Shared Encoder and Decoder.
Modelling of Bi-Directional Spatio-Temporal Dependence and Users' Dynamic Preferences for Missing POI Check-In Identification.
Improving Domain-Specific Classification by Collaborative Learning with Adaptation Networks.
Point Cloud Processing via Recurrent Set Encoding.
Uncovering Specific-Shape Graph Anomalies in Attributed Graphs.
How Does Knowledge of the AUC Constrain the Set of Possible Ground-Truth Labelings?
Efficient Gaussian Process Classification Using Pólya-Gamma Data Augmentation.
RobustSTL: A Robust Seasonal-Trend Decomposition Algorithm for Long Time Series.
Exploiting Local Feature Patterns for Unsupervised Domain Adaptation.
Unified Embedding Alignment with Missing Views Inferring for Incomplete Multi-View Clustering.
Learning Compact Model for Large-Scale Multi-Label Data.
Non-Autoregressive Machine Translation with Auxiliary Regularization.
Universal Approximation Property and Equivalence of Stochastic Computing-Based Neural Networks and Binary Neural Networks.
Deep Metric Learning by Online Soft Mining and Class-Aware Attention.
Multiple Independent Subspace Clusterings.
Transferable Attention for Domain Adaptation.
Hyperbolic Heterogeneous Information Network Embedding.
Explainable Reasoning over Knowledge Graphs for Recommendation.
SCNN: A General Distribution Based Statistical Convolutional Neural Network with Application to Video Object Detection.
Robustness Can Be Cheap: A Highly Efficient Approach to Discover Outliers under High Outlier Ratios.
A Sharper Generalization Bound for Divide-and-Conquer Ridge Regression.
HyperAdam: A Learnable Task-Adaptive Adam for Network Training.
Scalable Distributed DL Training: Batching Communication and Computation.
An Efficient Approach to Informative Feature Extraction from Multimodal Data.
SVM-Based Deep Stacking Networks.
Orderly Subspace Clustering.
Theoretical Analysis of Label Distribution Learning.
Adversarial Binary Collaborative Filtering for Implicit Feedback.
Bounding Uncertainty for Active Batch Selection.
Video Inpainting by Jointly Learning Temporal Structure and Spatial Details.
CAMO: A Collaborative Ranking Method for Content Based Recommendation.
Robust Anomaly Detection in Videos Using Multilevel Representations.
Automatic Bayesian Density Analysis.
Predicting Urban Dispersal Events: A Two-Stage Framework through Deep Survival Analysis on Mobility Data.
Improving GAN with Neighbors Embedding and Gradient Matching.
Learning Triggers for Heterogeneous Treatment Effects.
Natural Option Critic.
Learning Competitive and Discriminative Reconstructions for Anomaly Detection.
A Non-Convex Optimization Approach to Correlation Clustering.
Clipped Matrix Completion: A Remedy for Ceiling Effects.
Holographic Factorization Machines for Recommendation.
A Radical-Aware Attention-Based Model for Chinese Text Classification.
Self-Paced Active Learning: Query the Right Thing at the Right Time.
An Integral Tag Recommendation Model for Textual Content.
Cross-View Local Structure Preserved Diversity and Consensus Learning for Multi-View Unsupervised Feature Selection.
Refining Coarse-Grained Spatial Data Using Auxiliary Spatial Data Sets with Various Granularities.
Coreset Stochastic Variance-Reduced Gradient with Application to Optimal Margin Distribution Machine.
Character n-Gram Embeddings to Improve RNN Language Models.
Variational Autoencoder with Implicit Optimal Priors.
Matrix Completion for Graph-Based Deep Semi-Supervised Learning.
Learning Vine Copula Models for Synthetic Data Generation.
Network Structure and Transfer Behaviors Embedding via Deep Prediction Model.
Non-Ergodic Convergence Analysis of Heavy-Ball Algorithms.
Multi-Precision Quantized Neural Networks via Encoding Decomposition of {-1, +1}.
Partial Multi-Label Learning by Low-Rank and Sparse Decomposition.
Soft Facial Landmark Detection by Label Distribution Learning.
On the Persistence of Clustering Solutions and True Number of Clusters in a Dataset.
Diversity-Driven Extensible Hierarchical Reinforcement Learning.
Hierarchical Context Enabled Recurrent Neural Network for Recommendation.
Composable Modular Reinforcement Learning.
Safe Policy Improvement with Baseline Bootstrapping in Factored Environments.
Unsupervised Transfer Learning for Spoken Language Understanding in Intelligent Agents.
Transferable Curriculum for Weakly-Supervised Domain Adaptation.
Sensitivity Analysis of Deep Neural Networks.
Evaluating Recommender System Stability with Influence-Guided Fuzzing.
Label Embedding with Partial Heterogeneous Contexts.
Sublinear Time Numerical Linear Algebra for Structured Matrices.
Automatic Code Review by Learning the Revision of Source Code.
Virtual-Taobao: Virtualizing Real-World Online Retail Environment for Reinforcement Learning.
Multi-View Anomaly Detection: Neighborhood in Locality Matters.
MEAL: Multi-Model Ensemble via Adversarial Learning.
Geometric Hawkes Processes with Graph Convolutional Recurrent Neural Networks.
Sparse Reject Option Classifier Using Successive Linear Programming.
Unsupervised Learning with Contrastive Latent Variable Models.
Congestion Graphs for Automated Time Predictions.
Granger-Causal Attentive Mixtures of Experts: Learning Important Features with Neural Networks.
Covariate Shift Adaptation on Learning from Positive and Unlabeled Data.
How Many Pairwise Preferences Do We Need to Rank a Graph Consistently?
Latent Multi-Task Architecture Learning.
Devil in the Details: Towards Accurate Single and Multiple Human Parsing.
RepeatNet: A Repeat Aware Neural Recommendation Machine for Session-Based Recommendation.
Deep Recurrent Survival Analysis.
On Fair Cost Sharing Games in Machine Learning.
Regularized Evolution for Image Classifier Architecture Search.
Explicitly Imposing Constraints in Deep Networks via Conditional Gradients Gives Improved Generalization and Faster Convergence.
Training Complex Models with Multi-Task Weak Supervision.
Nearest-Neighbour-Induced Isolation Similarity and Its Impact on Density-Based Clustering.
Composite Binary Decomposition Networks.
Robust Optimization over Multiple Domains.
Learning to Solve NP-Complete Problems: A Graph Neural Network for Decision TSP.
Interpretable Preference Learning: A Game Theoretic Framework for Large Margin On-Line Feature and Rule Learning.
Exploiting Synthetically Generated Data with Semi-Supervised Learning for Small and Imbalanced Datasets.
Trainable Undersampling for Class-Imbalance Learning.
Adversarial Dropout for Recurrent Neural Networks.
On Reinforcement Learning for Full-Length Game of StarCraft.
Compressing Recurrent Neural Networks with Tensor Ring for Action Recognition.
Policy Optimization with Model-Based Explorations.
Non-Parametric Transformation Networks for Learning General Invariances from Data.
Determinantal Reinforcement Learning.
Biologically Motivated Algorithms for Propagating Local Target Representations.
Multigrid Backprojection Super-Resolution and Deep Filter Visualization.
Efficient Counterfactual Learning from Bandit Feedback.
Number Sequence Prediction Problems for Evaluating Computational Powers of Neural Networks.
Subspace Selection via DR-Submodular Maximization on Lattices.
ClusterGAN: Latent Space Clustering in Generative Adversarial Networks.
Weisfeiler and Leman Go Neural: Higher-Order Graph Neural Networks.
Cogra: Concept-Drift-Aware Stochastic Gradient Descent for Time-Series Forecasting.
A Probabilistic Derivation of LASSO and L12-Norm Feature Selections.
A Two-Stream Mutual Attention Network for Semi-Supervised Biomedical Segmentation with Noisy Labels.
Cost-Sensitive Learning to Rank.
Towards Better Interpretability in Deep Q-Networks.
DyS: A Framework for Mixture Models in Quantification.
A Distillation Approach to Data Efficient Individual Treatment Effect Estimation.
The Curse of Concentration in Robust Learning: Evasion and Poisoning Attacks from Concentration of Measure.
Complex Unitary Recurrent Neural Networks Using Scaled Cayley Transform.
LabelForest: Non-Parametric Semi-Supervised Learning for Activity Recognition.
State-Augmentation Transformations for Risk-Sensitive Reinforcement Learning.
A Comparative Analysis of Expected and Distributional Reinforcement Learning.
Distributed PageRank Computation: An Improved Theoretical Study.
Bias-Variance Trade-Off in Hierarchical Probabilistic Models Using Higher-Order Feature Interactions.
Robust Metric Learning on Grassmann Manifolds with Generalization Guarantees.
Orthogonality-Promoting Dictionary Learning via Bayesian Inference.
Scaling-Up Split-Merge MCMC with Locality Sensitive Sampling (LSS).
Relation Structure-Aware Heterogeneous Information Network Embedding.
Block Belief Propagation for Parameter Learning in Markov Random Fields.
Super Sparse Convolutional Neural Networks.
Guiding the One-to-One Mapping in CycleGAN via Optimal Transport.
GeniePath: Graph Neural Networks with Adaptive Receptive Paths.
Active Sampling for Open-Set Classification without Initial Annotation.
Adaptive Sparse Confidence-Weighted Learning for Online Feature Selection.
Ranking-Based Deep Cross-Modal Hashing.
Efficient and Effective Incomplete Multi-View Clustering.
The Utility of Sparse Representations for Control in Reinforcement Learning.
A Bandit Approach to Maximum Inner Product Search.
A Theoretically Guaranteed Deep Optimization Framework for Robust Compressive Sensing MRI.
Learning Multi-Task Communication with Message Passing for Sequence Learning.
Trust Region Evolution Strategies.
Scale Invariant Fully Convolutional Network: Detecting Hands Efficiently.
Near-Neighbor Methods in Random Preference Completion.
Learning Plackett-Luce Mixtures from Partial Preferences.
MFPCA: Multiscale Functional Principal Component Analysis.
Which Factorization Machine Modeling Is Better: A Theoretical Answer with Optimal Guarantee.
Non-Compensatory Psychological Models for Recommender Systems.
Evolutionary Manytasking Optimization Based on Symbiosis in Biocoenosis.
CircConv: A Structured Convolution with Low Complexity.
Learning Logistic Circuits.
Collaborative, Dynamic and Diversified User Profiling.
SepNE: Bringing Separability to Network Embedding.
Exploiting Coarse-to-Fine Task Transfer for Aspect-Level Sentiment Classification.
Learning Disentangled Representation with Pairwise Independence.
Towards Automated Semi-Supervised Learning.
Learning Adaptive Random Features.
Spectral Clustering in Heterogeneous Information Networks.
Robust Multi-Agent Reinforcement Learning via Minimax Deep Deterministic Policy Gradient.
Sign-Full Random Projections.
X-DMM: Fast and Scalable Model Based Text Clustering.
From Zero-Shot Learning to Cold-Start Recommendation.
Lifted Proximal Operator Machines.
Communication-Efficient Stochastic Gradient MCMC for Neural Networks.
Structural Causal Bandits with Non-Manipulable Variables.
Understanding Learned Models by Identifying Important Features at the Right Resolution.
Gradient-Based Inference for Networks with Output Constraints.
Accurate and Interpretable Factorization Machines.
TransConv: Relationship Embedding in Social Networks.
Unsupervised Domain Adaptation Based on Source-Guided Discrepancy.
Multi-Source Neural Variational Inference.
Unsupervised Domain Adaptation by Matching Distributions Based on the Maximum Mean Discrepancy via Unilateral Transformations.
On-Line Learning of Linear Dynamical Systems: Exponential Forgetting in Kalman Filters.
Active Generative Adversarial Network for Image Classification.
Exploiting Class Learnability in Noisy Data.
Mixture of Expert/Imitator Networks: Scalable Semi-Supervised Learning Framework.
Guided Dropout.
Similarity Learning via Kernel Preserving Embedding.
Dimension-Free Error Bounds from Random Projections.
Precision-Recall versus Accuracy and the Role of Large Data Sets.
DoPAMINE: Double-Sided Masked CNN for Pixel Adaptive Multiplicative Noise Despeckling.
Estimating the Days to Success of Campaigns in Crowdfunding: A Deep Survival Perspective.
SCFont: Structure-Guided Chinese Font Generation via Deep Stacked Networks.
Gaussian-Induced Convolution for Graphs.
Non-Asymptotic Uniform Rates of Consistency for k-NN Regression.
Fast Incremental SVDD Learning Algorithm with the Gaussian Kernel.
Joint Semi-Supervised Feature Selection and Classification through Bayesian Approach.
Multi-Dimensional Classification via kNN Feature Augmentation.
Tile2Vec: Unsupervised Representation Learning for Spatially Distributed Data.
Classification with Costly Features Using Deep Reinforcement Learning.
Model-Free IRL Using Maximum Likelihood Estimation.
Meta-Descent for Online, Continual Prediction.
Neural Collective Graphical Models for Estimating Spatio-Temporal Population Flow from Aggregated Data.
TAPAS: Train-Less Accuracy Predictor for Architecture Search.
Estimating the Causal Effect from Partially Observed Time Series.
Complex Moment-Based Supervised Eigenmap for Dimensionality Reduction.
Tensorial Change Analysis Using Probabilistic Tensor Regression.
Inter-Class Angular Loss for Convolutional Neural Networks.
Manifold-Valued Image Generation with Wasserstein Generative Adversarial Nets.
Large-Scale Heterogeneous Feature Embedding.
Bootstrap Estimated Uncertainty of the Environment Model for Model-Based Reinforcement Learning.
Efficient Identification of Approximate Best Configuration of Training in Large Datasets.
Efficient Quantization for Neural Networks with Binary Weights and Low Bitwidth Activations.
Multi-Fidelity Automatic Hyper-Parameter Tuning via Transfer Series Expansion.
One-Pass Incomplete Multi-View Clustering.
HERS: Modeling Influential Contexts with Heterogeneous Relations for Sparse and Cold-Start Recommendation.
Learning to Adaptively Scale Recurrent Neural Networks.
Learning Anytime Predictions in Neural Networks via Adaptive Loss Balancing.
Interaction-Aware Factorization Machines for Recommender Systems.
Multi-Task Deep Reinforcement Learning with PopArt.
The SpectACl of Nonconvex Clustering: A Spectral Approach to Density-Based Clustering.
Knowledge Transfer via Distillation of Activation Boundaries Formed by Hidden Neurons.
Knowledge Distillation with Adversarial Samples Supporting Decision Boundary.
Efficient and Scalable Multi-Task Regression on Massive Number of Tasks.
Temporal Anomaly Detection: Calibrating the Surprise.
Distributional Semantics Meets Multi-Label Learning.
Hybrid Reinforcement Learning with Expert State Sequences.
Smooth Deep Image Generator from Noises.
Non-Autoregressive Neural Machine Translation with Enhanced Decoder Input.
MixUp as Locally Linear Out-of-Manifold Regularization.
AFS: An Attention-Based Mechanism for Supervised Feature Selection.
Scalable and Efficient Pairwise Learning to Achieve Statistical Accuracy.
Using Benson's Algorithm for Regularization Parameter Tracking.
Interpretation of Neural Networks Is Fragile.
Eliminating Latent Discrimination: Train Then Mask.
Counting and Sampling from Markov Equivalent DAGs Using Clique Trees.
Spatiotemporal Multi-Graph Convolution Network for Ride-Hailing Demand Forecasting.
Off-Policy Deep Reinforcement Learning by Bootstrapping the Covariate Shift.
Incomplete Label Multi-Task Deep Learning for Spatio-Temporal Event Subtype Forecasting.
Wasserstein Soft Label Propagation on Hypergraphs: Algorithm and Generalization Error Bounds.
Explainable Recommendation through Attentive Multi-View Learning.
Towards Reliable Learning for High Stakes Applications.
Bayesian Posterior Approximation via Greedy Particle Optimization.
Fully Convolutional Network with Multi-Step Reinforcement Learning for Image Processing.
Efficient Data Point Pruning for One-Class SVM.
Combined Reinforcement Learning via Abstract Representations.
The Goldilocks Zone: Towards Better Understanding of Neural Network Loss Landscapes.
Transductive Bounds for the Multi-Class Majority Vote Classifier.
Hypergraph Neural Networks.
Collaboration Based Multi-Label Learning.
Partial Label Learning with Self-Guided Retraining.
Unsupervised Feature Selection by Pareto Optimization.
Improved Knowledge Graph Embedding Using Background Taxonomic Information.
Partial Multi-Label Learning via Credible Label Elicitation.
Controllable Image-to-Video Translation: A Case Study on Facial Expression Generation.
Human-Like Delicate Region Erasing Strategy for Weakly Supervised Detection.
How to Combine Tree-Search Methods in Reinforcement Learning.
Single-Label Multi-Class Image Classification by Deep Logistic Regression.
Multistream Classification with Relative Density Ratio Estimation.
On-Line Adaptative Curriculum Learning for GANs.
Approximate Kernel Selection with Strong Approximate Consistency.
Linear Kernel Tests via Empirical Likelihood for High-Dimensional Data.
Balanced Linear Contextual Bandits.
Inverse Abstraction of Neural Networks Using Symbolic Interpolation.
Learning Segmentation Masks with the Independence Prior.
Efficient Online Learning for Mapping Kernels on Linguistic Structures.
Spatially Invariant Unsupervised Object Detection with Convolutional Neural Networks.
Diverse Exploration via Conjugate Policies for Policy Gradient Methods.
Utilizing Class Information for Deep Network Representation Shaping.
End-to-End Safe Reinforcement Learning through Barrier Functions for Safety-Critical Continuous Control Tasks.
Image Block Augmentation for One-Shot Learning.
Tensor Decomposition for Multilayer Networks Clustering.
Embedding Uncertain Knowledge Graphs.
A Layer Decomposition-Recomposition Framework for Neuron Pruning towards Accurate Lightweight Networks.
Data-Adaptive Metric Learning with Scale Alignment.
EA-CG: An Approximate Second-Order Method for Training Fully-Connected Neural Networks.
Deep Neural Network Quantization via Layer-Wise Optimization Using Limited Training Data.
Distributionally Robust Semi-Supervised Learning for People-Centric Sensing.
Large-Scale Interactive Recommendation with Tree-Structured Policy Gradient.
Two-Stage Label Embedding via Neural Factorization Machine for Multi-Label Classification.
Joint Domain Alignment and Discriminative Feature Learning for Unsupervised Deep Domain Adaptation.
Disjoint Label Space Transfer Learning with Common Factorised Space.
Towards Non-Saturating Recurrent Units for Modelling Long-Term Dependencies.
Adversarial Learning of Semantic Relevance in Text to Image Synthesis.
Dynamic Learning of Sequential Choice Bandit Problem under Marketing Fatigue.
FRAME Revisited: An Interpretation View Based on Particle Evolution.
Deep Convolutional Sum-Product Networks.
CNN-Cert: An Efficient Framework for Certifying Robustness of Convolutional Neural Networks.
Online Learning from Data Streams with Varying Feature Spaces.
Enhanced Random Forest Algorithms for Partially Monotone Ordinal Classification.
Mode Variational LSTM Robust to Unseen Modes of Variation: Application to Facial Expression Recognition.
High Dimensional Clustering with r-nets.
Random Feature Maps for the Itemset Kernel.
Robust Negative Sampling for Network Embedding.
Adversarial Label Learning.
Hyperprior Induced Unsupervised Disentanglement of Latent Representations.
Attacking Data Transforming Learners at Training Time.
Character-Level Language Modeling with Deeper Self-Attention.
Model Learning for Look-Ahead Exploration in Continuous Control.
An Exponential Tail Bound for the Deleted Estimate.
State Abstraction as Compression in Apprenticeship Learning.
On Completing Sparse Knowledge Base with Transitive Relation Embedding.
Tracking Logical Difference in Large-Scale Ontologies: A Forgetting-Based Approach.
Recursively Learning Causal Structures Using Regression-Based Conditional Independence Test.
TransGate: Knowledge Graph Embedding with Shared Gate Structure.
Reasoning over Streaming Data in Metric Temporal Datalog.
Safe Partial Diagnosis from Normal Observations.
Iterated Belief Base Revision: A Dynamic Epistemic Logic Approach.
Amalgamating Knowledge towards Comprehensive Classification.
End-to-End Structure-Aware Convolutional Networks for Knowledge Base Completion.
Induction of Non-Monotonic Logic Programs to Explain Boosted Tree Models Using LIME.
An Open-World Extension to Knowledge Graph Completion Models.
Efficient Concept Induction for Description Logics.
ATOMIC: An Atlas of Machine Commonsense for If-Then Reasoning.
Belief Change and Non-Monotonic Reasoning Sans Compactness.
Blameworthiness in Strategic Games.
Declarative Question Answering over Knowledge Bases Containing Natural Language Text with Answer Set Programming.
On Limited Conjunctions and Partial Features in Parameter-Tractable Feature Logics.
Group Decision Diagram (GDD): A Compact Representation for Permutations.
Less but Better: Generalization Enhancement of Ordinal Embedding via Distributional Margin.
SDRL: Interpretable and Data-Efficient Deep Reinforcement Learning Leveraging Symbolic Planning.
Complexity of Inconsistency-Tolerant Query Answering in Datalog+/- under Cardinality-Based Repairs.
Implanting Rational Knowledge into Distributed Representation at Morpheme Level.
SAT-Based Explicit LTLf Satisfiability Checking.
Reasoning over Assumption-Based Argumentation Frameworks via Direct Answer Set Programming Encodings.
Multi-Context System for Optimization Problems.
Representing and Learning Grammars in Answer Set Programming.
Combining Deep Learning and Qualitative Spatial Reasoning to Learn Complex Structures from Sparse Examples with Noise.
Ontology-Based Query Answering for Probabilistic Temporal Data.
LENA: Locality-Expanded Neural Embedding for Knowledge Base Completion.
Knowledge Refinement via Rule Selection.
Minimum Intervention Cover of a Causal Graph.
Bi-Kronecker Functional Decision Diagrams: A Novel Canonical Representation of Boolean Functions.
Modular Materialisation of Datalog Programs.
Partial Awareness.
Forgetting in Modular Answer Set Programming.
A Sequential Set Generation Method for Predicting Set-Valued Outputs.
Counting Complexity for Reasoning in Abstract Argumentation.
Disjunctive Normal Form for Multi-Agent Modal Logics Based on Logical Separability.
Strong Equivalence for Epistemic Logic Programs Made Easy.
Complexity of Abstract Argumentation under a Claim-Centric View.
On Structured Argumentation with Conditional Preferences.
Validation of Growing Knowledge Graphs by Abductive Text Evidences.
Qualitative Spatial Logic over 2D Euclidean Spaces Is Not Finitely Axiomatisable.
ABox Abduction via Forgetting in ALC.
Approximate Stream Reasoning with Metric Temporal Logic under Uncertainty.
Argumentation for Explainable Scheduling.
Identification of Causal Effects in the Presence of Selection Bias.
From Horn-SRIQ to Datalog: A Data-Independent Transformation That Preserves Assertion Entailment.
Model-Based Diagnosis for Cyber-Physical Production Systems Based on Machine Learning and Residual-Based Diagnosis Models.
Querying Attributed DL-Lite Ontologies Using Provenance Semirings.
Ontology-Mediated Query Answering over Log-Linear Probabilistic Data.
Learning Features and Abstract Actions for Computing Generalized Plans.
Enhancing Lazy Grounding with Lazy Normalization in Answer-Set Programming.
Weighted Abstract Dialectical Frameworks through the Lens of Approximation Fixpoint Theory.
Abstracting Causal Models.
Extension Removal in Abstract Argumentation - An Axiomatic Approach.
Certifying the True Error: Machine Learning in Coq with Verified Generalization Guarantees.
Relaxing and Restraining Queries for OBDA.
Unbounded Orchestrations of Transducers for Manufacturing.
Satisfiability in Strategy Logic Can Be Easier than Model Checking.
Preference-Aware Task Assignment in Spatial Crowdsourcing.
CycleEmotionGAN: Emotional Semantic Consistency Preserved CycleGAN for Adapting Image Emotions.
Consensual Affine Transformations for Partial Valuation Aggregation.
Be Inaccurate but Don't Be Indecisive: How Error Distribution Can Affect User Experience.
Goal-Oriented Dialogue Policy Learning from Failures.
Lipper: Synthesizing Thy Speech Using Multi-View Lipreading.
Human Motion Prediction via Learning Local Structure Representations and Temporal Dependencies.
Election with Bribed Voter Uncertainty: Hardness and Approximation Algorithm.
AI-Sketcher : A Deep Generative Model for Producing High-Quality Sketches.
Deep Transformation Method for Discriminant Analysis of Multi-Channel Resting State fMRI.
Interactive Semantic Parsing for If-Then Recipes via Hierarchical Reinforcement Learning.
FLEX: Faithful Linguistic Explanations for Neural Net Based Model Decisions.
Augmenting Markov Decision Processes with Advising.
Learning Models of Sequential Decision-Making with Partial Specification of Agent Behavior.
Generation of Policy-Level Explanations for Reinforcement Learning.
Geometry-Aware Face Completion and Editing.
Deep Neural Networks Constrained by Decision Rules.
RGBD Based Gaze Estimation via Multi-Task CNN.
A Unified Framework for Planning in Adversarial and Cooperative Environments.
Task Transfer by Preference-Based Cost Learning.
Efficiently Combining Human Demonstrations and Interventions for Safe Training of Autonomous Systems in Real-Time.
Counterfactual Randomization: Rescuing Experimental Studies from Obscured Confounding.
Verifying Robustness of Gradient Boosted Models.
Human-in-the-Loop Feature Selection.
Updates in Human-AI Teams: Understanding and Addressing the Performance/Compatibility Tradeoff.
Making Money from What You Know - How to Sell Information?
One-Network Adversarial Fairness.
Fuzzy-Classification Assisted Solution Preselection in Evolutionary Optimization.
An Improved Generic Bet-and-Run Strategy with Performance Prediction for Stochastic Local Search.
Bounded Suboptimal Search with Learned Heuristics for Multi-Agent Systems.
Enriching Non-Parametric Bidirectional Search Algorithms.
Allocating Planning Effort When Actions Expire.
Stepping Stones to Inductive Synthesis of Low-Level Looping Programs.
Pareto Optimization for Subset Selection with Dynamic Cost Constraints.
Evolving Solutions to Community-Structured Satisfiability Formulas.
Real-Time Planning as Decision-Making under Uncertainty.
Evolving Action Abstractions for Real-Time Planning in Extensive-Form Games.
On the Time Complexity of Algorithm Selection Hyper-Heuristics for Multimodal Optimisation.
Fine-Grained Search Space Classification for Hard Enumeration Variants of Subset Problems.
Bézier Simplex Fitting: Describing Pareto Fronts of Simplicial Problems with Small Samples in Multi-Objective Optimization.
Running Time Analysis of MOEA/D with Crossover on Discrete Optimization Problem.
On the Optimal Efficiency of Cost-Algebraic A.
Heuristic Search Algorithm for Dimensionality Reduction Optimally Combining Feature Selection and Feature Extraction.
Greedy Maximization of Functions with Bounded Curvature under Partition Matroid Constraints.
A Two-Individual Based Evolutionary Algorithm for the Flexible Job Shop Scheduling Problem.
Distributionally Adversarial Attack.
Preference-Aware Task Assignment in On-Demand Taxi Dispatching: An Online Stable Matching Approach.
A PAC Framework for Aggregating Agents' Judgments.
A Better Algorithm for Societal Tradeoffs.
A Unified Approach to Online Matching with Conflict-Aware Constraints.
Defending Elections against Malicious Spread of Misinformation.
Poll-Confident Voters in Iterative Voting.
Random Walk Decay Centrality.
Practical Algorithms for Multi-Stage Voting Rules with Parallel Universes Tiebreaking.
A Framework for Approval-Based Budgeting Methods.
Learning Deviation Payoffs in Simulation-Based Games.
Mechanism Design for Multi-Type Housing Markets with Acceptable Bundles.
Variance Reduction in Monte Carlo Counterfactual Regret Minimization (VR-MCCFR) for Extensive Form Games Using Baselines.
Learning Optimal Strategies to Commit To.
Fairly Allocating Many Goods with Few Queries.
Deception in Finitely Repeated Security Games.
Optimal Dynamic Auctions Are Virtual Welfare Maximizers.
Quasi-Perfect Stackelberg Equilibrium.
When Do Envy-Free Allocations Exist?
Dynamic Contracting under Positive Commitment.
Revenue Enhancement via Asymmetric Signaling in Interdependent-Value Auctions.
Cooperation Enforcement and Collusion Resistance in Repeated Public Goods Games.
Heuristic Voting as Ordinal Dominance Strategies.
"Reverse Gerrymandering": Manipulation in Multi-Group Decision Making.
Approximate Inference of Outcomes in Probabilistic Elections.
Forming Probably Stable Communities with Limited Interactions.
Pareto-Optimal Allocation of Indivisible Goods with Connectivity Constraints.
Object Reachability via Swaps along a Line.
Solving Partially Observable Stochastic Games with Public Observations.
On the Inducibility of Stackelberg Equilibrium for Security Games.
Computing the Yolk in Spatial Voting Games without Computing Median Lines.
You Get What You Share: Incentives for a Sharing Economy.
Deep Bayesian Trust: A Dominant and Fair Incentive Mechanism for Crowd.
Pareto Efficient Auctions with Interest Rates.
On the Distortion Value of the Elections with Abstention.
Multi-Unit Bilateral Trade.
Fair and Efficient Memory Sharing: Confronting Free Riders.
An Equivalence between Wagering and Fair-Division Mechanisms.
A Bridge between Liquid and Social Welfare in Combinatorial Auctions with Submodular Bidders.
Fair Knapsack.
Very Hard Electoral Control Problems.
An Improved Quasi-Polynomial Algorithm for Approximate Well-Supported Nash Equilibria.
Online Convex Optimization for Sequential Decision Processes and Extensive-Form Games.
How Similar Are Two Elections?
Approximation and Hardness of Shift-Bribery.
Random Dictators with a Random Referee: Constant Sample Complexity Mechanisms for Social Choice.
Online Pandora's Boxes and Bandits.
Balancing Relevance and Diversity in Online Bipartite Matching via Submodularity.
On the Complexity of the Inverse Semivalue Problem for Weighted Voting Games.
Solving Large Extensive-Form Games with Strategy Constraints.
Group Fairness for the Allocation of Indivisible Goods.
Randomized Wagering Mechanisms.
Partial Verification as a Substitute for Money.
Solving Imperfect-Information Games via Discounted Regret Minimization.
Fast Iterative Combinatorial Auctions via Bayesian Learning.
Walrasian Dynamics in Multi-Unit Markets.
Primarily about Primaries.
On Rational Delegations in Liquid Democracy.
Low-Distortion Social Welfare Functions.
Convergence of Learning Dynamics in Information Retrieval Games.
From Recommendation Systems to Facility Location Games.
Generalized Distance Bribery.
Unknown Agents in Friends Oriented Hedonic Games: Stability and Complexity.
On the Proximity of Markets with Integral Equilibria.
Pareto Optimal Allocation under Compact Uncertain Preferences.
Fair Division with a Secretive Agent.
The Pure Price of Anarchy of Pool Block Withholding Attacks in Bitcoin Mining.
Learning to Write Stories with Thematic Consistency and Wording Novelty.
3D Face Synthesis Driven by Personality Impression.
Regular Boardgames.
Tackling Sparse Rewards in Real-Time Games with Statistical Forward Planning Methods.
Generalized Batch Normalization: Towards Accelerating Deep Neural Networks.
Optimizing in the Dark: Learning an Optimal Solution through a Simple Request Interface.
Adding Constraints to Bayesian Inverse Problems.
Melding the Data-Decisions Pipeline: Decision-Focused Learning for Combinatorial Optimization.
Task Embedded Coordinate Update: A Realizable Framework for Multivariate Non-Convex Optimization.
Low-Rank Semidefinite Programming for the MAX2SAT Problem.
Asynchronous Proximal Stochastic Gradient Algorithm for Composition Optimization Problems.
Learning Optimal Classification Trees Using a Binary Linear Program Formulation.
Bayesian Functional Optimisation with Shape Prior.
Concurrency Debugging with MaxSMT.
Algorithms for Average Regret Minimization.
BIRD: Engineering an Efficient CNF-XOR SAT Solver and Its Applications to Approximate Model Counting.
A PSPACE Subclass of Dependency Quantified Boolean Formulas and Its Effective Solving.
Revisiting Projection-Free Optimization for Strongly Convex Constraint Sets.
On Sampling Complexity of the Semidefinite Affine Rank Feasibility Problem.
Automatic Construction of Parallel Portfolios via Explicit Instance Grouping.
Adaptive Proximal Average Based Variance Reducing Stochastic Methods for Optimization with Composite Regularization.
RSA: Byzantine-Robust Stochastic Aggregation Methods for Distributed Learning from Heterogeneous Datasets.
A Recursive Algorithm for Projected Model Counting.
Asynchronous Delay-Aware Accelerated Proximal Coordinate Descent for Nonconvex Nonsmooth Problems.
Separator-Based Pruned Dynamic Programming for Steiner Tree.
Abduction-Based Explanations for Machine Learning Models.
Faster Gradient-Free Proximal Stochastic Methods for Nonconvex Nonsmooth Optimization.
Constraint-Based Sequential Pattern Mining with Decision Diagrams.
Stochastic Submodular Maximization with Performance-Dependent Item Costs.
Solving Integer Quadratic Programming via Explicit and Structural Restrictions.
A Nonconvex Projection Method for Robust PCA.
On Geometric Alignment in Low Doubling Dimension.
Model-Based Diagnosis of Hybrid Systems Using Satisfiability Modulo Theory.
Improving Optimization Bounds Using Machine Learning: Decision Diagrams Meet Deep Reinforcement Learning.
A SAT+CAS Approach to Finding Good Matrices: New Examples and Counterexamples.
Clairvoyant Restarts in Branch-and-Bound Search Using Online Tree-Size Estimation.
Learning Optimal and Fair Decision Trees for Non-Discriminative Decision-Making.
A Deep Neural Network for Unsupervised Anomaly Detection and Diagnosis in Multivariate Time Series Data.
Deep Reinforcement Learning for Green Security Games with Real-Time Information.
A Deep Reinforcement Learning Framework for Rebalancing Dockless Bike Sharing Systems.
Interpretable Predictive Modeling for Climate Variables with Weighted Lasso.
Deep Bayesian Optimization on Attributed Graphs.
Modelling Autobiographical Memory Loss across Life Span.
Simulation-Based Approach to Efficient Commonsense Reasoning in Very Large Knowledge Bases.
Scalable Recollections for Continual Lifelong Learning.
Attentive Tensor Product Learning.
Human-Like Sketch Object Recognition via Analogical Learning.
MPD-AL: An Efficient Membrane Potential Driven Aggregate-Label Learning Algorithm for Spiking Neurons.
TDSNN: From Deep Neural Networks to Deep Spike Neural Networks with Temporal-Coding.
Direct Training for Spiking Neural Networks: Faster, Larger, Better.
Cognitive Deficit of Deep Learning in Numerosity.
DeepDPM: Dynamic Population Mapping via Deep Neural Network.
One-Class Adversarial Nets for Fraud Detection.
SAFE: A Neural Survival Analysis Model for Fraud Early Detection.
Incorporating Semantic Similarity with Geographic Correlation for Query-POI Relevance Learning.
Optimal Interdiction of Urban Criminals with the Aid of Real-Time Information.
MetaStyle: Three-Way Trade-off among Speed, Flexibility, and Quality in Neural Style Transfer.
Learning Phenotypes and Dynamic Patient Representations via RNN Regularized Collective Non-Negative Tensor Factorization.
TET-GAN: Text Effects Transfer via Stylization and Destylization.
A2-Net: Molecular Structure Estimation from Cryo-EM Density Volumes.
On Strength Adjustment for MCTS-Based Programs.
G2C: A Generator-to-Classifier Framework Integrating Multi-Stained Visual Cues for Pathological Glomerulus Classification.
Hierarchical Macro Strategy Model for MOBA Game AI.
Functional Connectivity Network Analysis with Discriminative Hub Detection for Brain Disease Identification.
Private Model Compression via Knowledge Distillation.
Differentially Private Empirical Risk Minimization with Smooth Non-Convex Loss Functions: A Non-Stationary View.
PerformanceNet: Score-to-Audio Music Generation with Multi-Band Convolutional Residual Network.
Exploiting the Contagious Effect for Employee Turnover Prediction.
Improving Search with Supervised Learning in Trick-Based Card Games.
Subtask Gated Networks for Non-Intrusive Load Monitoring.
Spatiality Preservable Factored Poisson Regression for Large-Scale Fine-Grained GPS-Based Population Analysis.
The Kelly Growth Optimal Portfolio with Ensemble Learning.
GAMENet: Graph Augmented MEmory Networks for Recommending Medication Combination.
PhoneMD: Learning to Diagnose Parkinson's Disease from Smartphone Data.
NeVAE: A Deep Generative Model for Molecular Graphs.
Building Causal Graphs from Medical Literature and Electronic Medical Records.
Pathological Evidence Exploration in Deep Retinal Image Diagnosis.
Difficulty-Aware Attention Network with Confidence Learning for Medical Image Segmentation.
Scalable Robust Kidney Exchange.
AffinityNet: Semi-Supervised Few-Shot Learning for Disease Type Prediction.
Play as You Like: Timbre-Enhanced Multi-Modal Music Style Transfer.
Molecular Property Prediction: A Multilevel Quantum Interactions Modeling Perspective.
DeepFuzz: Automatic Generation of Syntax Valid C Programs for Fuzz Testing.
Joint Representation Learning for Multi-Modal Transportation Recommendation.
Perceptual-Sensitive GAN for Generating Adversarial Patches.
DeepSTN+: Context-Aware Spatial-Temporal Neural Network for Crowd Flow Prediction in Metropolis.
SEGAN: Structure-Enhanced Generative Adversarial Network for Compressed Sensing MRI Reconstruction.
Learning Heterogeneous Spatial-Temporal Representation for Bike-Sharing Demand Prediction.
Adversarial Learning for Weakly-Supervised Social Network Alignment.
Traffic Updates: Saying a Lot While Revealing a Little.
Crash to Not Crash: Learn to Identify Dangerous Vehicles Using a Simulator.
A Memetic Approach for Sequential Security Games on a Plane with Moving Targets.
Connecting the Digital and Physical World: Improving the Robustness of Adversarial Attacks.
Combo-Action: Training Agent For FPS Game with Auxiliary Tasks.
Cash-Out User Detection Based on Attributed Heterogeneous Information Network with a Hierarchical Attention Mechanism.
Exploiting Sentence Embedding for Medical Question Answering.
Deep Reinforcement Learning for Syntactic Error Repair in Student Programs.
Attention Based Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting.
VidyutVanika: A Reinforcement Learning Based Broker Agent for a Power Trading Competition.
Efficient Region Embedding with Multi-View Spatial Networks: A Perspective of Locality-Constrained Spatial Autocorrelations.
Turbo Learning Framework for Human-Object Interactions Recognition and Human Pose Estimation.
Dynamic Spatial-Temporal Graph Convolutional Neural Networks for Traffic Forecasting.
Deriving Subgoals Autonomously to Accelerate Learning in Sparse Reward Domains.
Region-Based Message Exploration over Spatio-Temporal Data Streams.
Synergistic Image and Feature Adaptation: Towards Cross-Modality Domain Adaptation for Medical Image Segmentation.
Predicting Concrete and Abstract Entities in Modern Poetry.
Deep Latent Generative Models for Energy Disaggregation.
Beyond Speech: Generalizing D-Vectors for Biometric Verification.
Adversarial Unsupervised Representation Learning for Activity Time-Series.
Exploiting Time-Series Image-to-Image Translation to Expand the Range of Wildlife Habitat Analysis.
A Neural Multi-Task Learning Framework to Jointly Model Medical Named Entity Recognition and Normalization.
Weakly-Supervised Simultaneous Evidence Identification and Segmentation for Automated Glaucoma Diagnosis.
EnsNet: Ensconce Text in the Wild.
Detecting Incongruity between News Headline and Body Text via a Deep Hierarchical Encoder.
Zero Shot Learning for Code Education: Rubric Sampling with Deep Learning Inference.
DeepETA: A Spatial-Temporal Sequential Neural Network Model for Estimating Time of Arrival in Package Delivery System.
Bidirectional Inference Networks: A Class of Deep Bayesian Networks for Health Profiling.
Forbidden Nodes Aware Community Search.
Knowledge Tracing Machines: Factorization Machines for Knowledge Tracing.
AutoZOOM: Autoencoder-Based Zeroth Order Optimization Method for Attacking Black-Box Neural Networks.
A Study of Educational Data Mining: Evidence from a Thai University.
Hotels-50K: A Global Hotel Recognition Dataset.
Axiomatic Characterization of Data-Driven Influence Measures for Classification.
Learning to Address Health Inequality in the United States with a Bayesian Decision Network.
Multi3Net: Segmenting Flooded Buildings via Fusion of Multiresolution, Multisensor, and Multitemporal Satellite Imagery.
Emergency Department Online Patient-Caregiver Scheduling.
A Model-Free Affective Reinforcement Learning Approach to Personalization of an Autonomous Social Robot Companion for Early Literacy Education.
Image Aesthetic Assessment Assisted by Attributes through Adversarial Learning.
Violence Rating Prediction from Movie Scripts.
Convex Formulations for Fair Principal Component Analysis.
Who Blames Whom in a Crisis? Detecting Blame Ties from News Articles Using Neural Networks.
Deep Hierarchical Graph Convolution for Election Prediction from Geospatial Census Data.
Latent Dirichlet Allocation for Internet Price War.
ReAl-LiFE: Accelerating the Discovery of Individualized Brain Connectomes on GPUs.
Allocating Interventions Based on Predicted Outcomes: A Case Study on Homelessness Services.
Algorithms for Estimating Trends in Global Temperature Volatility.
Multi-GCN: Graph Convolutional Networks for Multi-View Networks, with Applications to Global Poverty.
Evolutionarily Learning Multi-Aspect Interactions and Influences from Network Structure and Node Content.
CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison.
Learning Diffusions without Timestamps.
HireNet: A Hierarchical Attention Model for the Automatic Analysis of Asynchronous Video Job Interviews.
Selecting Compliant Agents for Opt-in Micro-Tolling.
PGANs: Personalized Generative Adversarial Networks for ECG Synthesis to Improve Patient-Specific Deep ECG Classification.
Migration as Submodular Optimization.
Resisting Adversarial Attacks Using Gaussian Mixture Variational Autoencoders.
Optimal Surveillance of Covert Networks by Minimizing Inverse Geodesic Length.
Blameworthiness in Multi-Agent Settings.
Understanding Dropouts in MOOCs.
Bayesian Fairness.
Coverage Centrality Maximization in Undirected Networks.
Bias Reduction via End-to-End Shift Learning: Application to Citizen Science.
Gated Residual Recurrent Graph Neural Networks for Traffic Prediction.
Automatic Detection and Compression for Passive Acoustic Monitoring of the African Forest Elephant.
Predicting Hurricane Trajectories Using a Recurrent Neural Network.
Robust Online Matching with User Arrival Distribution Drift.
Addressing the Under-Translation Problem from the Entropy Perspective.
Regularizing Neural Machine Translation by Target-Bidirectional Agreement.
Hierarchical Reinforcement Learning for Course Recommendation in MOOCs.
Text Assisted Insight Ranking Using Context-Aware Memory Network.
Cross-Relation Cross-Bag Attention for Distantly-Supervised Relation Extraction.
Data Augmentation Based on Adversarial Autoencoder Handling Imbalance for Learning to Rank.
TransNFCM: Translation-Based Neural Fashion Compatibility Modeling.
Adversarial Training for Community Question Answer Selection Based on Multi-Scale Matching.
Context-Aware Self-Attention Networks.
Multi-View Information-Theoretic Co-Clustering for Co-Occurrence Data.
Multi-Interactive Memory Network for Aspect Based Multimodal Sentiment Analysis.
Structured and Sparse Annotations for Image Emotion Distribution Learning.
CISI-net: Explicit Latent Content Inference and Imitated Style Rendering for Image Inpainting.
Session-Based Recommendation with Graph Neural Networks.
Multi-Level Deep Cascade Trees for Conversion Rate Prediction in Recommendation System.
Community Focusing: Yet Another Query-Dependent Community Detection.
Community Detection in Social Networks Considering Topic Correlations.
UGSD: User Generated Sentiment Dictionaries from Online Customer Reviews.
VistaNet: Visual Aspect Attention Network for Multimodal Sentiment Analysis.
Entity Alignment between Knowledge Graphs Using Attribute Embeddings.
DeepTileBars: Visualizing Term Distribution for Neural Information Retrieval.
Meimei: An Efficient Probabilistic Approach for Semantically Annotating Tables.
Learning from Web Data Using Adversarial Discriminative Neural Networks for Fine-Grained Classification.
ATP: Directed Graph Embedding with Asymmetric Transitivity Preservation.
Surveys without Questions: A Reinforcement Learning Approach.
Mining Entity Synonyms with Efficient Neural Set Generation.
Unsupervised Neural Machine Translation with SMT as Posterior Regularization.
Multi-Perspective Relevance Matching with Hierarchical ConvNets for Social Media Search.
DTMT: A Novel Deep Transition Architecture for Neural Machine Translation.
SNR: Sub-Network Routing for Flexible Parameter Sharing in Multi-Task Learning.
Discrete Social Recommendation.
Popularity Prediction on Online Articles with Deep Fusion of Temporal Process and Content Features.
Personalized Question Routing via Heterogeneous Network Embedding.
Supervised User Ranking in Signed Social Networks.
Coupled CycleGAN: Unsupervised Hashing Network for Cross-Modal Retrieval.
Crawling the Community Structure of Multiplex Networks.
Incorporating Network Embedding into Markov Random Field for Better Community Detection.
Graph Convolutional Networks Meet Markov Random Fields: Semi-Supervised Community Detection in Attribute Networks.
Exploiting Background Knowledge in Compact Answer Generation for Why-Questions.
Learning to Align Question and Answer Utterances in Customer Service Conversation with Recurrent Pointer Networks.
Y2Seq2Seq: Cross-Modal Representation Learning for 3D Shape and Text by Joint Reconstruction and Prediction of View and Word Sequences.
Anchors Bring Ease: An Embarrassingly Simple Approach to Partial Multi-View Clustering.
Cooperative Multimodal Approach to Depression Detection in Twitter.
Feature Sampling Based Unsupervised Semantic Clustering for Real Web Multi-View Content.
Deeply Fusing Reviews and Contents for Cold Start Users in Cross-Domain Recommendation Systems.
Dynamic Layer Aggregation for Neural Machine Translation with Routing-by-Agreement.
Triple Classification Using Regions and Fine-Grained Entity Typing.
TableSense: Spreadsheet Table Detection with Convolutional Neural Networks.
DeepCF: A Unified Framework of Representation Learning and Matching Function Learning in Recommender System.
Dynamic Explainable Recommendation Based on Neural Attentive Models.
Answer Identification from Product Reviews for User Questions by Multi-Task Attentive Networks.
Improving One-Class Collaborative Filtering via Ranking-Based Implicit Regularizer.
ColNet: Embedding the Semantics of Web Tables for Column Type Prediction.
Comparative Document Summarisation via Classification.
Outlier Aware Network Embedding for Attributed Networks.
Incorporating Behavioral Constraints in Online AI Systems.
