KDD2019: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining

Author Index



Tagarelli, Andrea (University of Calabria)
	Tutorial~ Tutorial: Are You My Neighbor? Bringing Order to Neighbor Computing Problems.

Tai, Xiao Hui (Carnegie Mellon University)
	Applied Data Science Track~ Adversarial Matching of Dark Net Market Vendor Accounts

Takeuchi, Ichiro (Nagoya Institute of Technology & National Institute for Material Science & RIKEN Center for Advanced Intelligence Project)
	Research Track~ Learning Interpretable Metric between Graphs: Convex Formulation and Computation with Graph Mining

Taly, Ankur (Fiddler Labs)
	Tutorial~ Explainable AI in Industry

Tambe, Milind (University of Southern California)
	Applied Data Science Track~ Learning to Prescribe Interventions for Tuberculosis Patients Using Digital Adherence Data

Tan, Kian-Lee (National University of Singapore)
	Research Track~ Coresets for Minimum Enclosing Balls over Sliding Windows

Tan, Matthew (Stanford University)
	Applied Data Science Track~ Predicting Economic Development using Geolocated Wikipedia Articles

Tan, Qi (South China Normal University)
	Research Track~ Task-Adversarial Co-Generative Nets

Tan, Qiaoyu (Texas A&M University)
	Research Track~ Is a Single Vector Enough? Exploring Node Polysemy for Network Embedding

Tan, Qing (Alibaba Group)
	Applied Data Science Track~ Bid Optimization by Multivariable Control in Display Advertising

Tan, Sarah (Cornell University)
	Research Track~ Axiomatic Interpretability for Multiclass Additive Models

(Return to Top)


Tan, Shulong (Baidu Research)
	Research Track~ Hierarchical Multi-Task Word Embedding Learning for Synonym Prediction

Tanaka, Yusuke (NTT Corporation)
	Research Track~ Deep Mixture Point Processes: Spatio-temporal Event Prediction with Rich Contextual Information

Tanaka, Yuya (NTT DOCOMO, INC.)
	Applied Data Science Track~ Real-time On-Device Troubleshooting Recommendation for Smartphones

Tang, Fengyi (Michigan State University)
	Research Track~ Retaining Privileged Information for Multi-Task Learning
	Applied Data Science Track~ MetaPred: Meta-Learning for Clinical Risk Prediction with Limited Patient Electronic Health Records

Tang, Jian (DiDi AI Labs, Didi Chuxing & Syracuse University)
	Tutorial~ Deep Reinforcement Learning with Applications in Transportation

Tang, Jie (Tsinghua University)
	Research Track~ Representation Learning for Attributed Multiplex Heterogeneous Network
	Applied Data Science Track~ Infer Implicit Contexts in Real-time Online-to-Offline Recommendation
	Applied Data Science Track~ OAG: Toward Linking Large-scale Heterogeneous Entity Graphs
	Applied Data Science Track~ Sequential Scenario-Specific Meta Learner for Online Recommendation
	Applied Data Science Track~ Towards Knowledge-Based Personalized Product Description Generation in E-commerce
	Tutorial~ Learning From Networks: Algorithms, Theory, and Applications

Tang, Jiliang (Michigan State University)
	Research Track~ Graph Convolutional Networks with EigenPooling

Tang, Ke (Tsinghua University)
	Applied Data Science Track~ AlphaStock: A Buying-Winners-and-Selling-Losers Investment Strategy using Interpretable Deep Reinforcement Attention Networks

Tang, Xiaocheng (AI Labs, Didi Chuxing)
	Applied Data Science Track~ A Deep Value-network Based Approach for Multi-Driver Order Dispatching

Tang, Xiaoli (South China University of Technology)
	Applied Data Science Track~ AKUPM: Attention-Enhanced Knowledge-Aware User Preference Model for Recommendation

Tang, Yina (Facebook Inc.)
	Applied Data Science Track~ MSURU: Large Scale E-commerce Image Classification With Weakly Supervised Search Data

(Return to Top)


Tao, Dacheng (UBTECH Sydney AI Centre, SCS, University of Sydney)
	Research Track~ Multi-task Recurrent Neural Networks and Higher-order Markov Random Fields for Stock Price Movement Prediction: Multi-task RNN and Higer-order MRFs for Stock Price Classification

Tao, Jianrong (Fuxi AI Lab, NetEase Inc.)
	Applied Data Science Track~ MVAN: Multi-view Attention Networks for Real Money Trading Detection in Online Games

Tao, Zhiqiang (Northeastern University)
	Research Track~ Log2Intent: Towards Interpretable User Modeling via Recurrent Semantics Memory Unit

Tariq, Shahroz (The State University of New York (SUNY Korea))
	Applied Data Science Track~ Detecting Anomalies in Space using Multivariate Convolutional LSTM with Mixtures of Probabilistic PCA

Teo, Choon Hui (Amazon)
	Applied Data Science Track~ Semantic Product Search

Termier, Alexandre (Universite Rennes, Inria, CNRS, IRISA)
	Applied Data Science Track~ Towards Sustainable Dairy Management - A Machine Learning Enhanced Method for Estrus Detection

Thabault, Antoine (Verizon Media)
	Applied Data Science Track~ Recurrent Neural Networks for Stochastic Control in Real-Time Bidding

(Return to Top)


Thondikulam, Ganesh (Kaiser Permanente)
	Applied Data Science Invited Talk~ Analytics Journey Map: An Approach Enable to ML at Scale

Tian, Peng (Northeastern University)
	Applied Data Science Track~ A Severity Score for Retinopathy of Prematurity

Ting, Kai Ming (Federation University, Australia)
	Research Track~ Isolation Set-Kernel and Its Application to Multi-Instance Learning

Toda, Hiroyuki (NTT Corporation)
	Research Track~ Deep Mixture Point Processes: Spatio-temporal Event Prediction with Rich Contextual Information

Tokuda, Hideyuki (Keio University)
	Applied Data Science Track~ Real-World Product Deployment of Adaptive Push Notification Scheduling on Smartphones

Tokui, Seiya (Preferred Networks, Inc.)
	Applied Data Science Track~ Chainer: A Deep Learning Framework for Accelerating the Research Cycle

Tomkins, Andrew (Google Research)
	Applied Data Science Track~ Hard to Park? Estimating Parking Difficulty at Scale

(Return to Top)


Tong, Hanghang (Arizona State University)
	Research Track~ Task-Adversarial Co-Generative Nets

Tong, Jie (Microsoft)
	Applied Data Science Track~ Time-Series Anomaly Detection Service at Microsoft

Tong, Shiwei (University of Science and Technology of China)
	Research Track~ Exploiting Cognitive Structure for Adaptive Learning

Tong, Wei (University of Science and Technology of China)
	Research Track~ QuesNet: A Unified Representation for Heterogeneous Test Questions

Tong, Xialiang (Huawei Noah's Ark Lab)
	Applied Data Science Track~ A Data-Driven Approach for Multi-level Packing Problems in Manufacturing Industry

Tong, Xinran (Beihang University)
	Research Track~ Co-Prediction of Multiple Transportation Demands Based on Deep Spatio-Temporal Neural Network

Tong, Yongxin (Beihang University)
	Applied Data Science Track~ Hydra: A Personalized and Context-Aware Multi-Modal Transportation Recommendation System

(Return to Top)


Tran, Thien Q. (University of Tsukuba)
	Applied Data Science Track~ Seasonal-adjustment Based Feature Selection Method for Predicting Epidemic with Large-scale Search Engine Logs

Tran, Truyen (Deakin University)
	Research Track~ Graph Transformation Policy Network for Chemical Reaction Prediction

Trayvas, Baruch (Tech Yahoo)
	Applied Data Science Track~ Carousel Ads Optimization in Yahoo Gemini Native

Trister, Andrew (Apple Inc.)
	Applied Data Science Track~ Developing Measures of Cognitive Impairment in the Real World from Consumer-Grade Multimodal Sensor Streams

Tsang, Michael (University of Southern California)
	Research Track~ CoSTCo: A Neural Tensor Completion Model for Sparse Tensors

Tsay, Jackie (Google)
	Applied Data Science Track~ Gmail Smart Compose: Real-Time Assisted Writing

Tseng, Belle (Apple Inc.)
	Applied Data Science Track~ Developing Measures of Cognitive Impairment in the Real World from Consumer-Grade Multimodal Sensor Streams

Tsogsuren, Iveel (Google Research)
	Applied Data Science Track~ Hard to Park? Estimating Parking Difficulty at Scale

(Return to Top)


Tsubouchi, Kota (Yahoo Japan Corporation)
	Applied Data Science Track~ Predicting Evacuation Decisions using Representations of Individuals' Pre-Disaster Web Search Behavior
	Applied Data Science Track~ Real-World Product Deployment of Adaptive Push Notification Scheduling on Smartphones

Tu, Ke (Tsinghua University)
	Research Track~ AutoNE: Hyperparameter Optimization for Massive Network Embedding

Tu, Wei-Wei (4Paradigm Inc.)
	Applied Data Science Track~ AutoCross: Automatic Feature Crossing for Tabular Data in Real-World Applications

Tu, Ye (LinkedIn Corporation)
	Applied Data Science Track~ Feedback Shaping: A Modeling Approach to Nurture Content Creation

Tummalacherla, Meghasyam (Sage Bionetworks)
	Research Track~ A Permutation Approach to Assess Confounding in Machine Learning Applications for Digital Health

Tur, Gokhan (Uber AI)
	Applied Data Science Track~ OCC: A Smart Reply System for Efficient In-App Communications

Turnbull, Bradley C. (Airbnb Inc.)
	Applied Data Science Track~ Applying Deep Learning to Airbnb Search

(Return to Top)


Tuzhilin, Alexander (New York University)
	Applied Data Science Track~ E.T.-RNN: Applying Deep Learning to Credit Loan Applications

Tzeng, Eric (Pinterest & University of California, Berkeley)
	Applied Data Science Track~ Learning a Unified Embedding for Visual Search at Pinterest

Tziortziotis, Nikolaos (Tradelab and LRI, Université Paris-Sud)
	Tutorial~ Adaptive Influence Maximization

Udell, Madeleine (Cornell University)
	Research Track~ OBOE: Collaborative Filtering for AutoML Model Selection

Ueda, Naonori (NTT Corporation)
	Research Track~ Deep Mixture Point Processes: Spatio-temporal Event Prediction with Rich Contextual Information

Uenishi, Kota (Preferred Networks, Inc.)
	Applied Data Science Track~ Chainer: A Deep Learning Framework for Accelerating the Research Cycle

Ukkusuri, Satish V. (Purdue University)
	Applied Data Science Track~ Predicting Evacuation Decisions using Representations of Individuals' Pre-Disaster Web Search Behavior

Umerenkov, Dmitrii (Sberbank AI Lab)
	Applied Data Science Track~ E.T.-RNN: Applying Deep Learning to Credit Loan Applications

(Return to Top)


Uzkent, Burak (Stanford University)
	Applied Data Science Track~ Predicting Economic Development using Geolocated Wikipedia Articles

van den Hengel, Anton (University of Adelaide)
	Research Track~ Deep Anomaly Detection with Deviation Networks

Van Haaren, Jan (SciSports)
	Applied Data Science Track~ Actions Speak Louder than Goals: Valuing Player Actions in Soccer

Vandin, Fabio (Università di Padova)
	Research Track~ SPuManTE: Significant Pattern Mining with Unconditional Testing
	Tutorial~ Hypothesis Testing and Statistically-sound Pattern Mining

Vantini, Giovanna (Qatar Computing Research Institute)
	Research Track~ Time Critic Policy Gradient Methods for Traffic Signal Control in Complex and Congested Scenarios

Varadarajan, Balakrishnan (Google Research)
	Applied Data Science Track~ Large-Scale Training Framework for Video Annotation

(Return to Top)


Venkataraman, Shobha (Unaffiliated)
	Applied Data Science Track~ Towards Identifying Impacted Users in Cellular Services

Venkatesh, Svetha (Deakin University)
	Research Track~ Graph Transformation Policy Network for Chemical Reaction Prediction

Verma, Saurabh (University of Minnesota Twin Cities)
	Research Track~ Stability and Generalization of Graph Convolutional Neural Networks

Vermeer, Lukas (Booking.com)
	Applied Data Science Track~ Diagnosing Sample Ratio Mismatch in Online Controlled Experiments: A Taxonomy and Rules of Thumb for Practitioners

Vishwanathan, S V N (Amazon.com)
	Applied Data Science Track~ Whole Page Optimization with Global Constraints
	Research Track~ Scaling Multinomial Logistic Regression via Hybrid Parallelism

Vogel, Brian (Preferred Networks, Inc.)
	Applied Data Science Track~ Chainer: A Deep Learning Framework for Accelerating the Research Cycle

Vogel, Hadas (Tech Yahoo)
	Applied Data Science Track~ Carousel Ads Optimization in Yahoo Gemini Native

Vogelsong, Michael (Amazon)
	Applied Data Science Track~ Seeker: Real-Time Interactive Search

(Return to Top)


Voisin, Maxime (Stanford University)
	Applied Data Science Track~ Ambulatory Atrial Fibrillation Monitoring Using Wearable Photoplethysmography with Deep Learning

Vreeken, Jilles (CISPA Helmholtz Center for Information Security)
	Research Track~ Identifiability of Cause and Effect using Regularized Regression

Vreeken, Jilles (Saarland Informatics Campus)
	Tutorial~ Modern MDL meets Data Mining Insights, Theory, and Practice

Vucetic, Slobodan (Temple University)
	Applied Data Science Track~ How to Invest my Time: Lessons from Human-in-the-Loop Entity Extraction

Wagstaff, Kiri L. (California Institute of Technology)
	Applied Data Science Track~ Enabling Onboard Detection of Events of Scientific Interest for the Europa Clipper Spacecraft

Wahedi, Laila (Georgetown University)
	Applied Data Science Track~ Blending Noisy Social Media Signals with Traditional Movement Variables to Predict Forced Migration

Wang, Beidou (Simon Fraser University)
	Applied Data Science Track~ Personalized Attraction Enhanced Sponsored Search with Multi-task Learning

Wang, Bin (University of Technology Sydney & Southwest Jiaotong University)
	Applied Data Science Track~ Deep Uncertainty Quantification: A Machine Learning Approach for Weather Forecasting

Wang, Bo (Alibaba Group)
	Research Track~ A Minimax Game for Instance based Selective Transfer Learning

Wang, Chang-Dong (Sun Yat-sen University)
	Research Track~ EdMot: An Edge Enhancement Approach for Motif-aware Community Detection

Wang, Chaoyue (Platform and Content Group, Tencent)
	Applied Data Science Track~ A User-Centered Concept Mining System for Query and Document Understanding at Tencent

(Return to Top)


Wang, Cheng-Long (School of Computer Science and Center for OPTical IMagery Analysis and Learning (OPTIMAL), Northwestern Polytechnical University)
	Research Track~ K-Multiple-Means: A Multiple-Means Clustering Method with Specified K Clusters

Wang, Chenxu (Xi'an Jiaotong University)
	Research Track~ A Memory-Efficient Sketch Method for Estimating High Similarities in Streaming Sets

Wang, Chi (Microsoft Research)
	Research Track~ Fast Approximation of Empirical Entropy via Subsampling

Wang, Chong (S&P Global)
	Applied Data Science Track~ Reserve Price Failure Rate Prediction with Header Bidding in Display Advertising

Wang, Daheng (University of Notre Dame)
	Research Track~ TUBE: Embedding Behavior Outcomes for Predicting Success

Wang, Deng-Bao (Southwest University)
	Research Track~ Adaptive Graph Guided Disambiguation for Partial Label Learning

Wang, Fei (Weill Cornell Medicine)
	Research Track~ Dynamical Origins of Distribution Functions
	Research Track~ Retaining Privileged Information for Multi-Task Learning
	Research Track~ Uncovering Pattern Formation of Information Flow
	Applied Data Science Track~ MetaPred: Meta-Learning for Clinical Risk Prediction with Limited Patient Electronic Health Records
	Tutorial~ Learning From Networks: Algorithms, Theory, and Applications

Wang, Guoren (Beijing Institute of Technology)
	Research Track~ Three-Dimensional Stable Matching Problem for Spatial Crowdsourcing Platforms

Wang, Hao (Alibaba AI Labs)
	Research Track~ Enhancing Collaborative Filtering with Generative Augmentation
	Research Track~ MCNE: An End-to-End Framework for Learning Multiple Conditional Network Representations of Social Network

Wang, Hao (Alibaba Group)
	Applied Data Science Track~ Bid Optimization by Multivariable Control in Display Advertising

Wang, Hongning (University of Virginia)
	Research Track~ Factorization Bandits for Online Influence Maximization

(Return to Top)


Wang, Hongwei (Stanford University)
	Research Track~ Knowledge-aware Graph Neural Networks with Label Smoothness Regularization for Recommender Systems

Wang, Huazheng (University of Virginia)
	Research Track~ Factorization Bandits for Online Influence Maximization

Wang, Jia (AT&T Labs -- Research)
	Applied Data Science Track~ Towards Identifying Impacted Users in Cellular Services

Wang, Jing (The University of Tokyo)
	Applied Data Science Track~ Glaucoma Progression Prediction Using Retinal Thickness via Latent Space Linear Regression

Wang, Jingyuan (Beihang University)
	Research Track~ Empowering A* Search Algorithms with Neural Networks for Personalized Route Recommendation
	Applied Data Science Track~ AlphaStock: A Buying-Winners-and-Selling-Losers Investment Strategy using Interpretable Deep Reinforcement Attention Networks

Wang, Junxiang (George Mason University)
	Research Track~ ADMM for Efficient Deep Learning with Global Convergence

Wang, Kuansan (Microsoft Research)
	Applied Data Science Track~ OAG: Toward Linking Large-scale Heterogeneous Entity Graphs

Wang, Mengdi (University of Pittsburgh)
	Applied Data Science Track~ Smart Roles: Inferring Professional Roles in Email Networks

Wang, Mengshuo (4Paradigm Inc.)
	Applied Data Science Track~ AutoCross: Automatic Feature Crossing for Tabular Data in Real-World Applications

(Return to Top)


Wang, Peng (AI Labs, Didi Chuxing)
	Applied Data Science Track~ Automatic Dialogue Summary Generation for Customer Service

Wang, Pengfei (CNIC, Chinese Academy of Sciences)
	Research Track~ Automating Feature Subspace Exploration via Multi-Agent Reinforcement Learning

Wang, Pengyang (Missouri University of Science and Technology)
	Research Track~ Adversarial Substructured Representation Learning for Mobile User Profiling
	Research Track~ Unifying Inter-region Autocorrelation and Intra-region Structures for Spatial Embedding via Collective Adversarial Learning

Wang, Pengyun (Noah's Ark Lab, Huawei Technologies)
	Research Track~ Predicting Path Failure In Time-Evolving Graphs

Wang, Pinghui (Xi'an Jiaotong University)
	Research Track~ A Memory-Efficient Sketch Method for Estimating High Similarities in Streaming Sets

Wang, Qinyong (The University of Queensland)
	Research Track~ Enhancing Collaborative Filtering with Generative Augmentation
	Research Track~ Streaming Session-based Recommendation

Wang, Ruhan (Ancestry)
	Applied Data Science Track~ Ranking in Genealogy: Search Results Fusion at Ancestry

Wang, Shijin (iFLYTEK CO., LTD & State Key Laboratory of Cognitive Intelligence)
	Research Track~ Exploiting Cognitive Structure for Adaptive Learning
	Research Track~ QuesNet: A Unified Representation for Heterogeneous Test Questions

Wang, Suhang (Penn State University)
	Research Track~ dEFEND: Explainable Fake News Detection
	Research Track~ Graph Convolutional Networks with EigenPooling

(Return to Top)


Wang, Tengyun (South China University of Technology)
	Applied Data Science Track~ AKUPM: Attention-Enhanced Knowledge-Aware User Preference Model for Recommendation

Wang, Wei (University of California Los Angeles)
	Research Track~ Universal Representation Learning of Knowledge Bases by Jointly Embedding Instances and Ontological Concepts

Wang, Weifeng (Shanghai Jiaotong University)
	Research Track~ Urban Traffic Prediction from Spatio-Temporal Data Using Deep Meta Learning

Wang, Wensheng (JD.com)
	Applied Data Science Track~ Multi-Horizon Time Series Forecasting with Temporal Attention Learning

Wang, Xiang (National University of Singapore)
	Research Track~ KGAT: Knowledge Graph Attention Network for Recommendation

Wang, Xiaobo (Alibaba Inc.)
	Applied Data Science Track~ Buying or Browsing?: Predicting Real-time Purchasing Intent using Attention-based Deep Network with Multiple Behavior

Wang, Xiaowei (Alibaba Group)
	Applied Data Science Track~ Sequential Scenario-Specific Meta Learner for Online Recommendation

Wang, Xin (Tsinghua University)
	Research Track~ Social Recommendation with Optimal Limited Attention

(Return to Top)


Wang, Xisen (Alibaba Group)
	Research Track~ A Minimax Game for Instance based Selective Transfer Learning

Wang, Xuanhui (Google Inc.)
	Applied Data Science Track~ Combining Decision Trees and Neural Networks for Learning-to-Rank in Personal Search
	Applied Data Science Track~ TF-Ranking: Scalable TensorFlow Library for Learning-to-Rank

Wang, Xuechun (Shanghai Jiao Tong University)
	Research Track~ Separated Trust Regions Policy Optimization Method

Wang, Xuezhi (Google Research)
	Research Track~ Contextual Fact Ranking and Its Applications in Table Synthesis and Compression

Wang, Yan (Tsinghua University)
	Applied Data Science Track~ OAG: Toward Linking Large-scale Heterogeneous Entity Graphs

Wang, Yanchen (Georgetown University)
	Applied Data Science Track~ Blending Noisy Social Media Signals with Traditional Movement Variables to Predict Forced Migration

Wang, Yang (Tencent)
	Applied Data Science Track~ Large-scale User Visits Understanding and Forecasting with Deep Spatial-Temporal Tensor Factorization Framework

Wang, Yanhao (National University of Singapore)
	Research Track~ Coresets for Minimum Enclosing Balls over Sliding Windows

Wang, Yaqing (State University of New York at Buffalo)
	Research Track~ Hypothesis Generation From Text Based On Co-Evolution Of Biomedical Concepts

Wang, Yi (Google Research)
	Applied Data Science Track~ Hard to Park? Estimating Parking Difficulty at Scale

(Return to Top)


Wang, Yinan (Google)
	Applied Data Science Track~ Gmail Smart Compose: Real-Time Assisted Writing

Wang, Yuandong (Beihang University)
	Research Track~ Origin-Destination Matrix Prediction via Graph Convolution: a New Perspective of Passenger Demand Modeling

Wang, Yue (Tsinghua University)
	Research Track~ ?Opt: Learn to Regularize Recommender Models in Finer Levels

Wang, Yujing (Microsoft)
	Applied Data Science Track~ Time-Series Anomaly Detection Service at Microsoft

Wang, Yuyang (AWS AI Labs)
	Tutorial~ Forecasting Big Time Series: Theory and Practice

Wang, Zhaodong (Washington State University)
	Applied Data Science Track~ A Deep Value-network Based Approach for Multi-Driver Order Dispatching

Wang, Zhaonan (National Institute of Advanced Industrial Science and Technology)
	Applied Data Science Track~ DeepUrbanEvent: A System for Predicting Citywide Crowd Dynamics at Big Events

Wang, Zhaowen (Adobe Research)
	Research Track~ Log2Intent: Towards Interpretable User Modeling via Recurrent Semantics Memory Unit

Wang, Zhen (The Ohio State University)
	Research Track~ SurfCon: Synonym Discovery on Privacy-Aware Clinical Data

(Return to Top)


Wang, Zheng (Nanyang Technological University)
	Research Track~ Effective and Efficient Sports Play Retrieval with Deep Representation Learning

Wang, Zhongyuan (Meituan-Dianping Group)
	Research Track~ Knowledge-aware Graph Neural Networks with Label Smoothness Regularization for Recommender Systems

Ward, Logan (University of Chicago & Argonne National Lab)
	Applied Data Science Track~ IRNet: A General Purpose Deep Residual Regression Framework for Materials Discovery

Warlop, Romain (fifty-five)
	Research Track~ Tensorized Determinantal Point Processes for Recommendation

Wee, Wemer M. (NEC Corporation)
	Applied Data Science Track~ TV Advertisement Scheduling by Learning Expert Intentions

Wei, Dong (New Jersey Institute of Technology)
	Research Track~ Optimizing Peer Learning in Online Groups with Affinities

Wei, Hua (Pennsylvania State University)
	Research Track~ PressLight: Learning Max Pressure Control to Coordinate Traffic Signals in Arterial Network

Wei, Li (Google)
	Applied Data Science Track~ Fairness in Recommendation Ranking through Pairwise Comparisons

Wei, Yifang (Georgetown University)
	Applied Data Science Track~ Blending Noisy Social Media Signals with Traditional Movement Variables to Predict Forced Migration

(Return to Top)


Wei, Zhewei (Renmin University of China)
	Research Track~ Scalable Graph Embeddings via Sparse Transpose Proximities

Weimer, Markus (Microsoft)
	Applied Data Science Track~ Machine Learning at Microsoft with ML.NET

Wen, Jiawei (The Pennsylvania State University)
	Research Track~ ET-Lasso: A New Efficient Tuning of Lasso-type Regularization for High-Dimensional Data

Weng, Paul (Shanghai Jiao Tong University)
	Research Track~ Dual Sequential Prediction Models Linking Sequential Recommendation and Information Dissemination

Weng, Wei-Hung (Massachusetts Institute of Technology)
	Applied Data Science Track~ Unsupervised Clinical Language Translation

Weng, Yue (Uber AI)
	Applied Data Science Track~ OCC: A Smart Reply System for Efficient In-App Communications

Westing, Brandt (Apple Inc)
	Applied Data Science Track~ Raise to Speak: An Accurate, Low-power Detector for Activating Voice Assistants on Smartwatches

Wilder, Bryan (University of Southern California)
	Applied Data Science Track~ Learning to Prescribe Interventions for Tuberculosis Patients Using Digital Adherence Data

Wo, Tianyu (Beihang University)
	Research Track~ Origin-Destination Matrix Prediction via Graph Convolution: a New Perspective of Passenger Demand Modeling

Wolf, Stephan (Google)
	Applied Data Science Track~ TF-Ranking: Scalable TensorFlow Library for Learning-to-Rank

(Return to Top)


Wolverton, Christopher (Northwestern University)
	Applied Data Science Track~ IRNet: A General Purpose Deep Residual Regression Framework for Materials Discovery

Woo, Simon S. (Sungkyunkwan University)
	Applied Data Science Track~ Detecting Anomalies in Space using Multivariate Convolutional LSTM with Mixtures of Probabilistic PCA

Wu, Chuhan (Tsinghua University)
	Applied Data Science Track~ NPA: Neural News Recommendation with Personalized Attention

Wu, Di (Alibaba Group)
	Applied Data Science Track~ Bid Optimization by Multivariable Control in Display Advertising

Wu, Di (JD.com)
	Applied Data Science Track~ Multi-Horizon Time Series Forecasting with Temporal Attention Learning

Wu, Fangzhao (Microsoft Research Asia)
	Applied Data Science Track~ NPA: Neural News Recommendation with Personalized Attention

Wu, Han (University of Science and Technology of China)
	Research Track~ MCNE: An End-to-End Framework for Learning Multiple Conditional Network Representations of Social Network

Wu, Hao-Yu (Pinterest)
	Applied Data Science Track~ Learning a Unified Embedding for Visual Search at Pinterest

Wu, Jia (Macquarie University)
	Research Track~ Link Prediction with Signed Latent Factors in Signed Social Networks

(Return to Top)


Wu, Jing-Han (Southeast University & Ministry of Education)
	Research Track~ Disambiguation Enabled Linear Discriminant Analysis for Partial Label Dimensionality Reduction

Wu, Jun (Arizona State University)
	Research Track~ DEMO-Net: Degree-specific Graph Neural Networks for Node and Graph Classification

Wu, Junjie (Beihang University)
	Applied Data Science Track~ AlphaStock: A Buying-Winners-and-Selling-Losers Investment Strategy using Interpretable Deep Reinforcement Attention Networks

Wu, Kan (Pennsylvania State University)
	Research Track~ PressLight: Learning Max Pressure Control to Coordinate Traffic Signals in Arterial Network

Wu, Le (Hefei University of Technology)
	Research Track~ Automating Feature Subspace Exploration via Multi-Agent Reinforcement Learning

Wu, Lingfei (IBM Research)
	Research Track~ Efficient Global String Kernel with Random Features: Beyond Counting Substructures
	Research Track~ Scalable Global Alignment Graph Kernel Using Random Features: From Node Embedding to Graph Embedding

Wu, Ning (Beihang University)
	Research Track~ Empowering A* Search Algorithms with Neural Networks for Personalized Route Recommendation

Wu, Qiang (University of Technology Sydney)
	Applied Data Science Track~ Sample Adaptive Multiple Kernel Learning for Failure Prediction of Railway Points

Wu, Qingyun (University of Virginia)
	Research Track~ Factorization Bandits for Online Influence Maximization

(Return to Top)


Wu, Qitian (Shanghai Jiao Tong University)
	Research Track~ Dual Sequential Prediction Models Linking Sequential Recommendation and Information Dissemination

Wu, Runze (Fuxi AI Lab, NetEase Inc.)
	Applied Data Science Track~ MVAN: Multi-view Attention Networks for Real Money Trading Detection in Online Games

Wu, Shiqi (LinkedIn)
	Applied Data Science Track~ Social Skill Validation at LinkedIn

Wu, Xian (University of Notre Dame)
	Applied Data Science Track~ Online Purchase Prediction via Multi-Scale Modeling of Behavior Dynamics

Wu, Yi (Google)
	Applied Data Science Track~ Fairness in Recommendation Ranking through Pairwise Comparisons

Wu, Yinghui (Washington State University & Pacific Northwest National Laboratory)
	Research Track~ Attribute-Driven Backbone Discovery

Wu, Yonghui (Google)
	Applied Data Science Track~ Gmail Smart Compose: Real-Time Assisted Writing

Wu, You (Google Research)
	Research Track~ Contextual Fact Ranking and Its Applications in Table Synthesis and Compression

Wu, Zhengtao (University of Science and Technology of China)
	Applied Data Science Track~ Large-scale User Visits Understanding and Forecasting with Deep Spatial-Temporal Tensor Factorization Framework

(Return to Top)


Xia, Long (JD.com)
	Research Track~ Off-policy Learning for Multiple Loggers
	Applied Data Science Track~ Reinforcement Learning to Optimize Long-term User Engagement in Recommender Systems

Xia, Tianqi (The University of Tokyo & National Institute of Advanced Industrial Science and Technology)
	Applied Data Science Track~ DeepUrbanEvent: A System for Predicting Citywide Crowd Dynamics at Big Events

Xia, Yinglong (Huawei)
	Research Track~ Scalable Global Alignment Graph Kernel Using Random Features: From Node Embedding to Graph Embedding
	Applied Data Science Invited Talk~ Roll of Unified Graph Analysis Platforms

Xia, Zenghua (Tsinghua University)
	Applied Data Science Track~ Characterizing and Detecting Malicious Accounts in Privacy-Centric Mobile Social Networks: A Case Study

Xiao, Cao (IQVIA)
	Research Track~ Retaining Privileged Information for Multi-Task Learning
	Tutorial~ Data Mining Methods for Drug Discovery and Development

Xiao, Keli (Stony Brook University)
	Research Track~ A Hierarchical Career-Path-Aware Neural Network for Job Mobility Prediction
	Research Track~ Enhancing Domain Word Embedding via Latent Semantic Imputation

Xiao, Wenyi (Hong Kong University of Science and Technology)
	Research Track~ Beyond Personalization: Social Content Recommendation for Creator Equality and Consumer Satisfaction

Xiao, Xiaokui (National University of Singapore)
	Applied Data Science Track~ Community Detection on Large Complex Attribute Network

(Return to Top)


Xiao, Zhili (Tencent)
	Applied Data Science Track~ Large-scale User Visits Understanding and Forecasting with Deep Spatial-Temporal Tensor Factorization Framework

Xie, Ming-Kun (Nanjing University of Aeronautics and Astronautics)
	Research Track~ Learning Class-Conditional GANs with Active Sampling

Xie, Xing (Microsoft Research Asia)
	Applied Data Science Track~ NPA: Neural News Recommendation with Personalized Attention

Xing, Chunxiao (Tsinghua University)
	Applied Data Science Track~ Investment Behaviors Can Tell What Inside: Exploring Stock Intrinsic Properties for Stock Trend Prediction

Xing, Tony (Microsoft)
	Applied Data Science Track~ Time-Series Anomaly Detection Service at Microsoft

Xing, Xin (Alibaba Group)
	Applied Data Science Track~ Deep Spatio-Temporal Neural Networks for Click-Through Rate Prediction

Xiong, Hui (Rutgers-The State University of New Jersey & Baidu Inc.)
	Research Track~ A Hierarchical Career-Path-Aware Neural Network for Job Mobility Prediction
	Research Track~ Adaptive Deep Models for Incremental Learning: Considering Capacity Scalability and Sustainability
	Research Track~ Adversarial Substructured Representation Learning for Mobile User Profiling
	Research Track~ Co-Prediction of Multiple Transportation Demands Based on Deep Spatio-Temporal Neural Network
	Research Track~ Multiple Relational Attention Network for Multi-task Learning
	Research Track~ The Impact of Person-Organization Fit on Talent Management: A Structure-Aware Convolutional Neural Network Approach
	Applied Data Science Track~ A Collaborative Learning Framework to Tag Refinement for Points of Interest
	Applied Data Science Track~ DuerQuiz: A Personalized Question Recommender System for Intelligent Job Interview
	Applied Data Science Track~ Hydra: A Personalized and Context-Aware Multi-Modal Transportation Recommendation System

Xiong, Zhang (Beihang University)
	Applied Data Science Track~ AlphaStock: A Buying-Winners-and-Selling-Losers Investment Strategy using Interpretable Deep Reinforcement Attention Networks

Xiongwei, Wu (Singapore Management University)
	Applied Data Science Track~ FoodAI: Food Image Recognition via Deep Learning for Smart Food Logging

Xu, Bi-Cun (Nanjing University)
	Research Track~ Isolation Set-Kernel and Its Application to Multi-Instance Learning

Xu, Bixiong (Microsoft)
	Applied Data Science Track~ Time-Series Anomaly Detection Service at Microsoft

(Return to Top)


Xu, Cheng (Koubei, Alibaba Group)
	Applied Data Science Track~ Infer Implicit Contexts in Real-time Online-to-Offline Recommendation

Xu, Hongteng (Infinia ML, Inc. & Duke University)
	Tutorial~ Modeling and Applications for Temporal Point Processes

Xu, Huan (Alibaba Group)
	Applied Data Science Track~ A Unified Framework for Marketing Budget Allocation

Xu, Jiaming (Alibaba Group)
	Applied Data Science Track~ POG: Personalized Outfit Generation for Fashion Recommendation at Alibaba iFashion

Xu, Jian (Alibaba Group)
	Applied Data Science Track~ Bid Optimization by Multivariable Control in Display Advertising

Xu, Jiang (AI Labs, Didi Chuxing)
	Applied Data Science Track~ Automatic Dialogue Summary Generation for Customer Service

Xu, Jie (University of Leeds)
	Research Track~ Origin-Destination Matrix Prediction via Graph Convolution: a New Perspective of Passenger Demand Modeling

Xu, Jiejun (HRL Laboratories, LLC)
	Research Track~ DEMO-Net: Degree-specific Graph Neural Networks for Node and Graph Classification

(Return to Top)


Xu, Jin (Baidu Research)
	Applied Data Science Track~ A Collaborative Learning Framework to Tag Refinement for Points of Interest

Xu, Kai (Shanghai Tianrang Intelligent Technology Co., Ltd)
	Research Track~ PressLight: Learning Max Pressure Control to Coordinate Traffic Signals in Arterial Network

Xu, Kun (IBM Research)
	Research Track~ Efficient Global String Kernel with Random Features: Beyond Counting Substructures
	Research Track~ Scalable Global Alignment Graph Kernel Using Random Features: From Node Embedding to Graph Embedding

Xu, Lan (Tencent)
	Applied Data Science Track~ Large-scale User Visits Understanding and Forecasting with Deep Spatial-Temporal Tensor Factorization Framework

Xu, Liangtao (Chinese Academy of Meteorological Sciences)
	Applied Data Science Track~ LightNet: A Dual Spatiotemporal Encoder Network Model for Lightning Prediction

Xu, Linchuan (The University of Tokyo)
	Applied Data Science Track~ Glaucoma Progression Prediction Using Retinal Thickness via Latent Space Linear Regression

Xu, Panpan (Bosch Research North America)
	Research Track~ Interpretable and Steerable Sequence Learning via Prototypes

(Return to Top)


Xu, Pinghua (Wuhan University & Macquarie University)
	Research Track~ Link Prediction with Signed Latent Factors in Signed Social Networks

Xu, Renzhe (Tsinghua University)
	Applied Data Science Track~ Uncovering the Co-driven Mechanism of Social and Content Links in User Churn Phenomena

Xu, Shunnan (Platform and Content Group, Tencent)
	Applied Data Science Track~ A User-Centered Concept Mining System for Query and Document Understanding at Tencent

Xu, Tao (Airbnb Inc.)
	Applied Data Science Track~ Applying Deep Learning to Airbnb Search

Xu, Tong (University of Science and Technology of China)
	Research Track~ MCNE: An End-to-End Framework for Learning Multiple Conditional Network Representations of Social Network
	Applied Data Science Track~ DuerQuiz: A Personalized Question Recommender System for Intelligent Job Interview

Xu, Wei (Tsinghua University)
	Research Track~ PrivPy: General and Scalable Privacy-Preserving Data Mining

Xu, Xinfeng (Virginia Tech)
	Research Track~ EpiDeep: Exploiting Embeddings for Epidemic Forecasting

Xu, Ya (Linkedin)
	Applied Data Science Invited Talk~ Data Science Challenges @ LinkedIn

Xu, Yu (Tencent)
	Applied Data Science Track~ A Deep Generative Approach to Search Extrapolation and Recommendation
	Applied Data Science Track~ A User-Centered Concept Mining System for Query and Document Understanding at Tencent

Xu, Zhe (Didi Chuxing)
	Applied Data Science Track~ A Deep Value-network Based Approach for Multi-Driver Order Dispatching

Xu, Zheng (Google Research)
	Applied Data Science Track~ Large-Scale Training Framework for Video Annotation

Xu, Zhenhui (Peking University)
	Research Track~ DeepGBM: A Deep Learning Framework Distilled by GBDT for Online Prediction Tasks

Xun, Guangxu (University of Virginia)
	Research Track~ Hypothesis Generation From Text Based On Co-Evolution Of Biomedical Concepts