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AAAI2019

Outlier Aware Network Embedding for Attributed Networks

Comparative Document Summarisation via Classification

ColNet: Embedding the Semantics of Web Tables for Column Type Prediction

Improving One-Class Collaborative Filtering via Ranking-Based Implicit Regularizer

Answer Identification from Product Reviews for User Questions by Multi-Task Attentive Networks

Dynamic Explainable Recommendation Based on Neural Attentive Models

TableSense: Spreadsheet Table Detection with Convolutional Neural Networks

Triple Classification Using Regions and Fine-Grained Entity Typing

Learning to Align Question and Answer Utterances in Customer Service Conversation with Recurrent Pointer Networks

Exploiting Background Knowledge in Compact Answer Generation for Why-Questions

Personalized Question Routing via Heterogeneous Network Embedding

Multi-Perspective Relevance Matching with Hierarchical ConvNets for Social Media Search

Unsupervised Neural Machine Translation with SMT as Posterior Regularization

Mining Entity Synonyms with Efficient Neural Set Generation

VistaNet: Visual Aspect Attention Network for Multimodal Sentiment Analysis

UGSD: User Generated Sentiment Dictionaries from Online Customer Reviews

Session-Based Recommendation with Graph Neural Networks

Multi-Interactive Memory Network for Aspect Based Multimodal Sentiment Analysis

Hierarchical Reinforcement Learning for Course Recommendation in MOOCs

Regularizing Neural Machine Translation by Target-Bidirectional Agreement

Addressing the Under-Translation Problem from the Entropy Perspective

Migration as Submodular Optimization

Evolutionarily Learning Multi-Aspect Interactions and Influences from Network Structure and Node Content

ReAl-LiFE: Accelerating the Discovery of Individualized Brain Connectomes on GPUs

Deep Hierarchical Graph Convolution for Election Prediction from Geospatial Census Data

Who Blames Whom in a Crisis? Detecting Blame Ties from News Articles Using Neural Networks

Violence Rating Prediction from Movie Scripts

Multi3Net: Segmenting Flooded Buildings via Fusion of Multiresolution, Multisensor, and Multitemporal Satellite Imagery

Learning to Address Health Inequality in the United States with a Bayesian Decision Network

Hotels-50K: A Global Hotel Recognition Dataset

AutoZOOM: Autoencoder-Based Zeroth Order Optimization Method for Attacking Black-Box Neural Networks

Knowledge Tracing Machines: Factorization Machines for Knowledge Tracing

Zero Shot Learning for Code Education: Rubric Sampling with Deep Learning Inference

Detecting Incongruity between News Headline and Body Text via a Deep Hierarchical Encoder

A Neural Multi-Task Learning Framework to Jointly Model Medical Named Entity Recognition and Normalization

Predicting Concrete and Abstract Entities in Modern Poetry

Synergistic Image and Feature Adaptation: Towards Cross-Modality Domain Adaptation for Medical Image Segmentation

Attention Based Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting

Connecting the Digital and Physical World: Improving the Robustness of Adversarial Attacks

DeepFuzz: Automatic Generation of Syntax Valid C Programs for Fuzz Testing

Play as You Like: Timbre-Enhanced Multi-Modal Music Style Transfer

Scalable Robust Kidney Exchange

Building Causal Graphs from Medical Literature and Electronic Medical Records

NeVAE: A Deep Generative Model for Molecular Graphs

GAMENet: Graph Augmented MEmory Networks for Recommending Medication Combination

PerformanceNet: Score-to-Audio Music Generation with Multi-Band Convolutional Residual Network

Private Model Compression via Knowledge Distillation

SAFE: A Neural Survival Analysis Model for Fraud Early Detection

One-Class Adversarial Nets for Fraud Detection

Constraint-Based Sequential Pattern Mining with Decision Diagrams

Faster Gradient-Free Proximal Stochastic Methods for Nonconvex Nonsmooth Optimization

Abduction-Based Explanations for Machine Learning Models

Separator-Based Pruned Dynamic Programming for Steiner Tree

BIRD: Engineering an Efficient CNF-XOR SAT Solver and Its Applications to Approximate Model Counting

Concurrency Debugging with MaxSMT

Learning Optimal Classification Trees Using a Binary Linear Program Formulation

Low-Rank Semidefinite Programming for the MAX2SAT Problem

Solving Imperfect-Information Games via Discounted Regret Minimization

Distributionally Adversarial Attack

Greedy Maximization of Functions with Bounded Curvature under Partition Matroid Constraints

Bézier Simplex Fitting: Describing Pareto Fronts of´ Simplicial Problems with Small Samples in Multi-Objective Optimization

Evolving Solutions to Community-Structured Satisfiability Formulas

Stepping Stones to Inductive Synthesis of Low-Level Looping Programs

Updates in Human-AI Teams: Understanding and Addressing the Performance/Compatibility Tradeoff

Counterfactual Randomization: Rescuing Experimental Studies from Obscured Confounding

Interactive Semantic Parsing for If-Then Recipes via Hierarchical Reinforcement Learning

Human Motion Prediction via Learning Local Structure Representations and Temporal Dependencies

Learning Features and Abstract Actions for Computing Generalized Plans

Approximate Stream Reasoning with Metric Temporal Logic under Uncertainty

LENA: Locality-Expanded Neural Embedding for Knowledge Base Completion

Combining Deep Learning and Qualitative Spatial Reasoning to Learn Complex Structures from Sparse Examples with Noise

SAT-Based Explicit LTLf Satisfiability Checking

Implanting Rational Knowledge into Distributed Representation at Morpheme Level

Less but Better: Generalization Enhancement of Ordinal Embedding via Distributional Margin

Group Decision Diagram (GDD): A Compact Representation for Permutations

Efficient Concept Induction for Description Logics

An Open-World Extension to Knowledge Graph Completion Models

End-to-End Structure-Aware Convolutional Networks for Knowledge Base Completion

Model Learning for Look-Ahead Exploration in Continuous Control

Character-Level Language Modeling with Deeper Self-Attention

Hyperprior Induced Unsupervised Disentanglement of Latent Representations

Robust Negative Sampling for Network Embedding

Enhanced Random Forest Algorithms for Partially Monotone Ordinal Classification

CNN-Cert: An Efficient Framework for Certifying Robustness of Convolutional Neural Networks

Adversarial Learning of Semantic Relevance in Text to Image Synthesis

Towards Non-Saturating Recurrent Units for Modelling Long-Term Dependencies

Joint Domain Alignment and Discriminative Feature Learning for Unsupervised Deep Domain Adaptation

Large-Scale Interactive Recommendation with Tree-Structured Policy Gradient

Deep Neural Network Quantization via Layer-Wise Optimization Using Limited Training Data

End-to-End Safe Reinforcement Learning through Barrier Functions for Safety-Critical Continuous Control Tasks

Utilizing Class Information for Deep Network Representation Shaping

Transductive Bounds for the Multi-Class Majority Vote Classifier

Combined Reinforcement Learning via Abstract Representations

Fully Convolutional Network with Multi-Step Reinforcement Learning for Image Processing

AFS: An Attention-Based Mechanism for Supervised Feature Selection

Temporal Anomaly Detection: Calibrating the Surprise

HERS: Modeling Influential Contexts with Heterogeneous Relations for Sparse and Cold-Start Recommendation

Manifold-Valued Image Generation with Wasserstein Generative Adversarial Nets

Model-Free IRL Using Maximum Likelihood Estimation

Similarity Learning via Kernel Preserving Embedding

On-Line Learning of Linear Dynamical Systems: Exponential Forgetting in Kalman Filters

Understanding Learned Models by Identifying Important Features at the Right Resolution

Learning Disentangled Representation with Pairwise Independence

Exploiting Coarse-to-Fine Task Transfer for Aspect-Level Sentiment Classification

Learning Logistic Circuits

Non-Compensatory Psychological Models for Recommender Systems

Bias-Variance Trade-Off in Hierarchical Probabilistic Models Using Higher-Order Feature Interactions

LabelForest: Non-Parametric Semi-Supervised Learning for Activity Recognition

Complex Unitary Recurrent Neural Networks Using Scaled Cayley Transform

Towards Better Interpretability in Deep Q-Networks

Weisfeiler and Leman Go Neural: Higher-Order Graph Neural Networks

ClusterGAN: Latent Space Clustering in Generative Adversarial Networks

Non-Parametric Transformation Networks for Learning General Invariances from Data

Adversarial Dropout for Recurrent Neural Networks

Interpretable Preference Learning: A Game Theoretic Framework for Large Margin On-Line Feature and Rule Learning

Learning to Solve NP-Complete Problems: A Graph Neural Network for Decision TSP

Nearest-Neighbour-Induced Isolation Similarity and Its Impact on Density-Based Clustering

Deep Recurrent Survival Analysis

RepeatNet: A Repeat Aware Neural Recommendation Machine for Session-Based Recommendation

Devil in the Details: Towards Accurate Single and Multiple Human Parsing

Latent Multi-Task Architecture Learning

Granger-Causal Attentive Mixtures of Experts: Learning Important Features with Neural Networks

Evaluating Recommender System Stability with Influence-Guided Fuzzing

Hierarchical Context Enabled Recurrent Neural Network for Recommendation

Diversity-Driven Extensible Hierarchical Reinforcement Learning

Soft Facial Landmark Detection by Label Distribution Learning

Character n-Gram Embeddings to Improve RNN Language Models

An Integral Tag Recommendation Model for Textual Content

A Radical-Aware Attention-Based Model for Chinese Text Classification

Learning Triggers for Heterogeneous Treatment Effects

Improving GAN with Neighbors Embedding and Gradient Matching

Automatic Bayesian Density Analysis

Robust Anomaly Detection in Videos Using Multilevel Representations

Robustness Can Be Cheap: A Highly Efficient Approach to Discover Outliers under High Outlier Ratios

Multiple Independent Subspace Clusterings

Non-Autoregressive Machine Translation with Auxiliary Regularization

Unified Embedding Alignment with Missing Views Inferring for Incomplete Multi-View Clustering

Efficient Gaussian Process Classification Using Pólya-Gamma Data Augmentation

Point Cloud Processing via Recurrent Set Encoding

Tied Transformers: Neural Machine Translation with Shared Encoder and Decoder

Multi-View Multi-Instance Multi-Label Learning Based on Collaborative Matrix Factorization

Data-Distortion Guided Self-Distillation for Deep Neural Networks

Confidence Weighted Multitask Learning

Revisiting Spatial-Temporal Similarity: A Deep Learning Framework for Traffic Prediction

Balanced Sparsity for Efficient DNN Inference on GPU

Multi-Order Attentive Ranking Model for Sequential Recommendation

RecurJac: An Efficient Recursive Algorithm for Bounding Jacobian Matrix of Neural Networks and Its Applications

ACE: An Actor Ensemble Algorithm for Continuous Control with Tree Search

QUOTA: The Quantile Option Architecture for Reinforcement Learning

Hashtag Recommendation for Photo Sharing Services

Find Me if You Can: Deep Software Clone Detection by Exploiting the Contest between the Plagiarist and the Detector

A New Ensemble Learning Framework for 3D Biomedical Image Segmentation

Deep Interest Evolution Network for Click-Through Rate Prediction

An Efficient Compressive Convolutional Network for Unified Object Detection and Image Compression

A Domain Generalization Perspective on Listwise Context Modeling

Aligning Domain-Specific Distribution and Classifier for Cross-Domain Classification from Multiple Sources

AutoSense Model for Word Sense Induction

Incorporating Structured Commonsense Knowledge in Story Completion

Transfer Learning for Sequence Labeling Using Source Model and Target Data

Implicit Argument Prediction as Reading Comprehension

Recurrent Stacking of Layers for Compact Neural Machine Translation Models

Joint Extraction of Entities and Overlapping Relations Using Position-Attentive Sequence Labeling

What Is One Grain of Sand in the Desert? Analyzing Individual Neurons in Deep NLP Models

Training Temporal Word Embeddings with a Compass

A Pattern-Based Approach to Recognizing Time Expressions

From Independent Prediction to Reordered Prediction: Integrating Relative Position and Global Label Information to Emotion Cause Identification

Hybrid Attention-Based Prototypical Networks for Noisy Few-Shot Relation Classification

Predicting and Analyzing Language Specificity in Social Media Posts

Generating Distractors for Reading Comprehension Questions from Real Examinations

MNCN: A Multilingual Ngram-Based Convolutional Network for Aspect Category Detection in Online Reviews

Deep Cascade Multi-Task Learning for Slot Filling in Online Shopping Assistant

Story Ending Generation with Incremental Encoding and Commonsense Knowledge

GIRNet: Interleaved Multi-Task Recurrent State Sequence Models

Document Informed Neural Autoregressive Topic Models with Distributional Prior

Neural Relation Extraction within and across Sentence Boundaries

Dictionary-Guided Editing Networks for Paraphrase Generation

Unsupervised Controllable Text Formalization

Dynamic Compositionality in Recursive Neural Networks with Structure-Aware Tag Representations

Dependency Grammar Induction with a Neural Variational Transition-Based Parser

A Unified Model for Opinion Target Extraction and Target Sentiment Prediction

Dialogue Generation: From Imitation Learning to Inverse Reinforcement Learning

Dependency or Span, End-to-End Uniform Semantic Role Labeling

Leveraging Web Semantic Knowledge in Word Representation Learning

FANDA: A Novel Approach to Perform Follow-Up Query Analysis

Unsupervised Post-Processing of Word Vectors via Conceptor Negation

LiveBot: Generating Live Video Comments Based on Visual and Textual Contexts

DialogueRNN: An Attentive RNN for Emotion Detection in Conversations

CGMH: Constrained Sentence Generation by Metropolis-Hastings Sampling

Combining Fact Extraction and Verification with Neural Semantic Matching Networks

Analyzing Compositionality-Sensitivity of NLI Models

HAS-QA: Hierarchical Answer Spans Model for Open-Domain Question Answering

Found in Translation: Learning Robust Joint Representations by Cyclic Translations between Modalities

Data-to-Text Generation with Content Selection and Planning

Zero-Shot Neural Transfer for Cross-Lingual Entity Linking

Learning Semantic Representations for Novel Words: Leveraging Both Form and Context

Challenges in the Automatic Analysis of Students’ Diagnostic Reasoning

GlobalTrait: Personality Alignment of Multilingual Word Embeddings

Fast PMI-Based Word Embedding with Efficient Use of Unobserved Patterns

A Grammar-Based Structural CNN Decoder for Code Generation

QUAREL: A Dataset and Models for Answering Questions about Qualitative Relationships

A Hierarchical Framework for Relation Extraction with Reinforcement Learning

Generating Live Soccer-Match Commentary from Play Data

Near-Lossless Binarization of Word Embeddings

CompareLDA: A Topic Model for Document Comparison

A Natural Language Corpus of Common Grounding under Continuous and Partially-Observable Context

Words Can Shift: Dynamically Adjusting Word Representations Using Nonverbal Behaviors

When Do Words Matter? Understanding the Impact of Lexical Choice on Audience Perception Using Individual Treatment Effect Estimation

Response Generation by Context-Aware Prototype Editing

Switch-Based Active Deep Dyna-Q: Efficient Adaptive Planning for Task-Completion Dialogue Policy Learning

Syntax-Aware Neural Semantic Role Labeling

Exploring Human-Like Reading Strategy for Abstractive Text Summarization

Graph Convolutional Networks for Text Classification

Plan-and-Write: Towards Better Automatic Storytelling

Combining Axiom Injection and Knowledge Base Completion for Efficient Natural Language Inference

Exploring Answer Stance Detection with Recurrent Conditional Attention

Bidirectional Transition-Based Dependency Parsing

Operator Mutexes and Symmetries for Simplifying Planning Tasks

Solving Multiagent Planning Problems with Concurrent Conditional Effects

Robustness Guarantees for Bayesian Inference with Gaussian Processes

On Testing of Uniform Samplers

Fast Relational Probabilistic Inference and Learning: Approximate Counting via Hypergraphs

Finding All Bayesian Network Structures within a Factor of Optimal

Personalized Robot Tutoring Using the Assistive Tutor POMDP (AT-POMDP)

BLOCK: Bilinear Superdiagonal Fusion for Visual Question Answering and Visual Relationship Detection

GaitSet: Regarding Gait as a Set for Cross-View Gait Recognition

I Know the Relationships: Zero-Shot Action Recognition via Two-Stream Graph Convolutional Networks and Knowledge Graphs

No-Reference Image Quality Assessment with Reinforcement Recursive List-Wise Ranking

Learning to Steer by Mimicking Features from Heterogeneous Auxiliary Networks

Gradient Harmonized Single-Stage Detector

Distribution Consistency Based Covariance Metric Networks for Few-Shot Learning

Robust Estimation of Similarity Transformation for Visual Object Tracking

PCGAN: Partition-Controlled Human Image Generation

Optimal Projection Guided Transfer Hashing for Image Retrieval

Spatial and Temporal Mutual Promotion for Video-Based Person Re-Identification

Deep Video Frame Interpolation Using Cyclic Frame Generation

Towards Highly Accurate and Stable Face Alignment for High-Resolution Videos

A Layer-Based Sequential Framework for Scene Generation with GANs

Learning Non-Uniform Hypergraph for Multi-Object Tracking

DeRPN: Taking a Further Step toward More General Object Detection

A Dual Attention Network with Semantic Embedding for Few-Shot Learning

Efficient Image Retrieval via Decoupling Diffusion into Online and Offline Processing

Learning a Visual Tracker from a Single Movie without Annotation

Tensor Ring Decomposition with Rank Minimization on Latent Space: An Efficient Approach for Tensor Completion

M2Det: A Single-Shot Object Detector Based on Multi-Level Feature Pyramid Network

DeBGUer: A Tool for Bug Prediction and Diagnosis

Automatic Generation of Chinese Short Product Titles for Mobile Display

Tagging Address Queries in Maps Search

Separating Wheat from Chaff: Joining Biomedical Knowledge and Patient Data for Repurposing Medications

Inferring Concept Prerequisite Relations from Online Educational Resources

Cleaning Noisy and Heterogeneous Metadata for Record Linking across Scholarly Big Datasets

Predicting Unsolvable Deals in the Birds of a Feather Solitaire Game

NeuroX: A Toolkit for Analyzing Individual Neurons in Neural Networks

Demo: Learning to Perceive Long-Range Obstacles Using Self-Supervision from Short-Range Sensors

Classifier-Agnostic Saliency Map Extraction