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MultiSumm: Towards a Unified Model for Multi-Lingual Abstractive Summarization

Efficient Heterogeneous Collaborative Filtering without Negative Sampling for Recommendation

Question-Driven Purchasing Propensity Analysis for Recommendation

Norm-Explicit Quantization: Improving Vector Quantization for Maximum Inner Product Search

Modeling Fluency and Faithfulness for Diverse Neural Machine Translation

Cross-Lingual Pre-Training Based Transfer for Zero-Shot Neural Machine Translation

Functionality Discovery and Prediction of Physical Objects

Understanding and Improving Proximity Graph Based Maximum Inner Product Search

Deep Match to Rank Model for Personalized Click-Through Rate Prediction

Modality to Modality Translation: An Adversarial Representation Learning and Graph Fusion Network for Multimodal Fusion

PEIA: Personality and Emotion Integrated Attentive Model for Music Recommendation on Social Media Platforms

Knowledge Graph Alignment Network with Gated Multi-Hop Neighborhood Aggregation

A Spherical Convolution Approach for Learning Long Term Viewport Prediction in 360 Immersive Video

Mining Unfollow Behavior in Large-Scale Online Social Networks via Spatial-Temporal Interaction

Who Likes What? – SplitLBI in Exploring Preferential Diversity of Ratings

A Recurrent Model for Collective Entity Linking with Adaptive Features

Unsupervised Detection of Sub-Events in Large Scale Disasters

A Distributed Multi-Sensor Machine Learning Approach to Earthquake Early Warning

Faking Fairness via Stealthily Biased Sampling

Lightweight and Robust Representation of Economic Scales from Satellite Imagery

Linguistic Fingerprints of Internet Censorship: the Case of Sina Weibo

On Identifying Hashtags in Disaster Twitter Data

Neural Approximate Dynamic Programming for On-Demand Ride-Pooling

Weak Supervision for Fake News Detection via Reinforcement Learning

Protecting Geolocation Privacy of Photo Collections

Weakly-Supervised Fine-Grained Event Recognition on Social Media Texts for Disaster Management

Doctor2Vec: Dynamic Doctor Representation Learning for Clinical Trial Recruitment

TrueLearn: A Family of Bayesian Algorithms to Match Lifelong Learners to Open Educational Resources

CONAN: Complementary Pattern Augmentation for Rare Disease Detection

CORE: Automatic Molecule Optimization Using Copy & Refine Strategy

Multi-Scale Anomaly Detection on Attributed Networks

CASTER: Predicting Drug Interactions with Chemical Substructure Representation

MRI Reconstruction with Interpretable Pixel-Wise Operations Using Reinforcement Learning

AdaCare: Explainable Clinical Health Status Representation Learning via Scale-Adaptive Feature Extraction and Recalibration

ConCare: Personalized Clinical Feature Embedding via Capturing the Healthcare Context

Gait Recognition for Co-Existing Multiple People Using Millimeter Wave Sensing

Generalizable Resource Allocation in Stream Processing via Deep Reinforcement Learning

OMuLeT: Online Multi-Lead Time Location Prediction for Hurricane Trajectory Forecasting

AirNet: A Calibration Model for Low-Cost Air Monitoring Sensors Using Dual Sequence Encoder Networks

MetaLight: Value-Based Meta-Reinforcement Learning for Traffic Signal Control

Dynamic Malware Analysis with Feature Engineering and Feature Learning

Tensorized LSTM with Adaptive Shared Memory for Learning Trends in Multivariate Time Series

Modelling and Solving Online Optimisation Problems

Smart Predict-and-Optimize for Hard Combinatorial Optimization Problems

Perpetual Voting: Fairness in Long-Term Decision Making

Asymptotic Risk of Bezier Simplex Fitting

Harnessing GANs for Zero-Shot Learning of New Classes in Visual Speech Recognition

Learning Graph Convolutional Network for Skeleton-Based Human Action Recognition by Neural Searching

BAR — A Reinforcement Learning Agent for Bounding-Box Automated Refinement

Cost-Accuracy Aware Adaptive Labeling for Active Learning

Path Ranking with Attention to Type Hierarchies

Commonsense Knowledge Base Completion with Structural and Semantic Context

Query Answering with Guarded Existential Rules under Stable Model Semantics

COTSAE: CO-Training of Structure and Attribute Embeddings for Entity Alignment

Information-Theoretic Understanding of Population Risk Improvement with Model Compression

Active Ordinal Querying for Tuplewise Similarity Learning

Data Programming Using Continuous and Quality-Guided Labeling Functions

Multi-View Clustering in Latent Embedding Space

Weakly Supervised Disentanglement by Pairwise Similaritie

Multi-View Clustering in Latent Embedding Space

Towards Better Forecasting by Fusing Near and Distant Future Visions

Adaptive Factorization Network: Learning Adaptive-Order Feature Interactions

Optimizing Discrete Spaces via Expensive Evaluations: A Learning to Search Framework

On the Discrepancy between the Theoretical Analysis and Practical Implementations of Compressed Communication for Distributed Deep Learning

Induction of Subgoal Automata for Reinforcement Learning

Diachronic Embedding for Temporal Knowledge Graph Completion

SNEQ: Semi-Supervised Attributed Network Embedding with Attention-Based Quantisation

An Attention-Based Graph Neural Network for Heterogeneous Structural Learning

DefogGAN: Predicting Hidden Information in the StarCraft Fog of War with Generative Adversarial Nets

InvNet: Encoding Geometric and Statistical Invariances in Deep Generative Models

Large-Scale Multi-View Subspace Clustering in Linear Time

A Unified Framework for Knowledge Intensive Gradient Boosting: Leveraging Human Experts for Noisy Sparse Domains

Residual Neural Processe

Solving General Elliptical Mixture Models through an Approximate Wasserstein Manifold

FlowScope: Spotting Money Laundering Based on Graphs

Collaborative Sampling in Generative Adversarial Networks

Learning from the Past: Continual Meta-Learning with Bayesian Graph Neural Networks

The HSIC Bottleneck: Deep Learning without Back-Propagation

Particle Filter Recurrent Neural Networks

Count-Based Exploration with the Successor Representation

Differentiable Reasoning on Large Knowledge Bases and Natural Language

Improved Knowledge Distillation via Teacher Assistant

A Bayesian Approach for Estimating Causal Effects from Observational Data

ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations

Stable Learning via Sample Reweighting

Efficient Facial Feature Learning with Wide Ensemble-Based Convolutional Neural Networks

Aggregated Learning: A Vector-Quantization Approach to Learning Neural Network Classifiers

Infomax Neural Joint Source-Channel Coding via Adversarial Bit Flip

Scalable Probabilistic Matrix Factorization with Graph-Based Priors

Bi-Objective Continual Learning: Learning ‘New’ While Consolidating ‘Known’

Network as Regularization for Training Deep Neural Networks: Framework, Model and Performance

Differential Equation Units: Learning Functional Forms of Activation Functions from Data

Fast and Efficient Boolean Matrix Factorization by Geometric Segmentation

Dual Relation Semi-Supervised Multi-Label Learning

Unsupervised Domain Adaptation via Structured Prediction Based Selective Pseudo-Labeling

Non-Local U-Nets for Biomedical Image Segmentation

Efficient Projection-Free Online Methods with Stochastic Recursive Gradient

Light Multi-Segment Activation for Model Compression

Scalable Decision-Theoretic Planning in Open and Typed Multiagent Systems

Fair Procedures for Fair Stable Marriage Outcomes

Generalized and Sub-Optimal Bipartite Constraints for Conflict-Based Search

Shapley Q-Value: A Local Reward Approach to Solve Global Reward Games

Story Realization: Expanding Plot Events into Sentences

Understanding the Semantic Content of Sparse Word Embeddings Using a Commonsense Knowledge Base

Unsupervised Domain Adaptation on Reading Comprehension

DMRM: A Dual-Channel Multi-Hop Reasoning Model for Visual Dialog

Schema-Guided Multi-Domain Dialogue State Tracking with Graph Attention Neural Networks

On Measuring and Mitigating Biased Inferences of Word Embeddings

P-SIF: Document Embeddings Using Partition Averaging

Controlling Neural Machine Translation Formality with Synthetic Supervision

Fine-Grained Entity Typing for Domain Independent Entity Linking

Translation-Based Matching Adversarial Network for Cross-Lingual Natural Language Inference

Target-Aspect-Sentiment Joint Detection for Aspect-Based Sentiment Analysis

Unsupervised Neural Dialect Translation with Commonality and Diversity Modeling

Evaluating Commonsense in Pre-Trained Language Models

Tandem Inference: An Out-of-Core Streaming Algorithm for Very Large-Scale Relational Inference

HAL: Improved Text-Image Matching by Mitigating Visual Semantic Hubs

Domain Generalization Using a Mixture of Multiple Latent Domains

FAS-Net: Construct Effective Features Adaptively for Multi-Scale Object Detection

Joint Super-Resolution and Alignment of Tiny Faces

Abstraction and Refinement in Games with Dynamic Weighted Terrain

Multi-Question Learning for Visual Question Answering

Object Instance Mining for Weakly Supervised Object Detection

Filtration and Distillation: Enhancing Region Attention for Fine-Grained Visual Categorization

Context-Aware Zero-Shot Recognition

Improved Visual-Semantic Alignment for Zero-Shot Object Detection

Temporal Interlacing Network

Cross-Modality Paired-Images Generation for RGB-Infrared Person Re-Identification

Task-Aware Monocular Depth Estimation for 3D Object Detection

Learning Diverse Stochastic Human-Action Generators by Learning Smooth Latent Transitions

Learning to Incorporate Structure Knowledge for Image Inpainting

Facial Action Unit Intensity Estimation via Semantic Correspondence Learning with Dynamic Graph Convolution

Pointwise Rotation-Invariant Network with Adaptive Sampling and 3D Spherical Voxel Convolution

Region Normalization for Image Inpainting

Rethinking the Image Fusion: A Fast Unified Image Fusion Network based on Proportional Maintenance of Gradient and Intensity

Find Objects and Focus on Highlights: Mining Object Semantics for Video Highlight Detection via Graph Neural Networks

Distance-IoU Loss: Faster and Better Learning for Bounding Box Regression

FASTER Recurrent Networks for Efficient Video Classification

Viewpoint-Aware Loss with Angular Regularization for Person Re-Identification

Refining HTN Methods via Task Insertion with Preferences

Uncertainty-Aware Search Framework for Multi-Objective Bayesian Optimization

Scalable Methods for Computing State Similarity in Deterministic Markov Decision Processes

A MaxSAT-Based Framework for Group Testing

Introducing Probabilistic Bezier Curves for N-Step Sequence Prediction

Adversarial Disentanglement with Grouped Observations

That and There: Judging the Intent of Pointing Actions with Robotic Arms

Zero-Shot Text-to-SQL Learning with Auxiliary Task

Hyperbolic Interaction Model for Hierarchical Multi-Label Classification

TemPEST: Soft Template-Based Personalized EDM Subject Generation through Collaborative Summarization

Open Domain Event Text Generation

TANDA: Transfer and Adapt Pre-Trained Transformer Models for Answer Sentence Selection

Predictive Engagement: An Efficient Metric for Automatic Evaluation of Open-Domain Dialogue Systems

Fine-Tuning by Curriculum Learning for Non-Autoregressive Neural Machine Translation

What Do You Mean ‘Why?’: Resolving Sluices in Conversations

Interactive Fiction Games: A Colossal Adventure

Emu: Enhancing Multilingual Sentence Embeddings with Semantic Specialization

Unsupervised Interlingual Semantic Representations from Sentence Embeddings for Zero-Shot Cross-Lingual Transfer

Knowledge-Enriched Visual Storytelling

What Makes A Good Story? Designing Composite Rewards for Visual Storytelling

Monolingual Transfer Learning via Bilingual Translators for Style-Sensitive Paraphrase Generation

Learning to Learn Morphological Inflection for Resource-Poor Languages

ICD Coding from Clinical Text Using Multi-Filter Residual Convolutional Neural Network

Why Attention? Analyze BiLSTM Deficiency and Its Remedies in the Case of NER

Span-Based Neural Buffer: Towards Efficient and Effective Utilization of Long-Distance Context for Neural Sequence Models

End-to-End Trainable Non-Collaborative Dialog System

Complementary Auxiliary Classifiers for Label-Conditional Text Generation

Global Greedy Dependency Parsing

MOSS: End-to-End Dialog System Framework with Modular Supervision

Discovering New Intents via Constrained Deep Adaptive Clustering with Cluster Refinement

Revision in Continuous Space: Unsupervised Text Style Transfer without Adversarial Learning

CatGAN: Category-Aware Generative Adversarial Networks with Hierarchical Evolutionary Learning for Category Text Generation

CAWA: An Attention-Network for Credit Attribution