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

Author Index


Gade, Krishna (Fiddler Labs)
	Tutorial~ Explainable AI in Industry

Gai, Kun (Alibaba Group)
	Applied Data Science Track~ Bid Optimization by Multivariable Control in Display Advertising
	Applied Data Science Track~ Practice on Long Sequential User Behavior Modeling for Click-Through Rate Prediction

Ganguly, Auroop (Northeastern University)
	Applied Data Science Track~ Nonparametric Mixture of Sparse Regressions on Spatio-Temporal Data -- An Application to Climate Prediction

Ganshin, Alexander (Yandex)
	Applied Data Science Track~ Precipitation Nowcasting with Satellite Imagery

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

Gao, Hongchang (University of Pittsburgh & JD Finance America Corporation)
	Research Track~ Conditional Random Field Enhanced Graph Convolutional Neural Networks
	Research Track~ ProGAN: Network Embedding via Proximity Generative Adversarial Network

Gao, Hongyang (Texas A&M University)
	Research Track~ Graph Representation Learning via Hard and Channel-Wise Attention Networks

Gao, Huiji (LinkedIn)
	Tutorial~ Deep Natural Language Processing for Search and Recommender Systems

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Gao, Jing (University at Buffalo)
	Tutorial~ Optimizing the Wisdom of the Crowd: Inference, Learning, and Teaching

Gao, Rong (Hubei University of Technology)
	Research Track~ DAML: Dual Attention Mutual Learning between Ratings and Reviews for Item Recommendation

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

Gao, Xin (King Abdullah University of Science and Technology)
	Research Track~ GCN-MF: Disease-Gene Association Identification By Graph Convolutional Networks and Matrix Factorization

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

Gartrell, Mike (Criteo AI Lab)
	Research Track~ Tensorized Determinantal Point Processes for Recommendation

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

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

Ge, Kaikai (WeiXin Group, Tencent Inc.)
	Applied Data Science Track~ Real-time Attention Based Look-alike Model for Recommender System

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Geng, Yangli-ao (Beijing Jiaotong University)
	Applied Data Science Track~ LightNet: A Dual Spatiotemporal Encoder Network Model for Lightning Prediction

Geyik, Sahin Cem (LinkedIn Corporation)
	Applied Data Science Track~ Fairness-Aware Ranking in Search & Recommendation Systems with Application to LinkedIn Talent Search
	Tutorial~ Explainable AI in Industry

Gionis, Aristides (Aalto University)
	Tutorial~ Mining Temporal Networks

Glass, Michael R. (IBM)
	Research Track~ Scalable Hierarchical Clustering with Tree Grafting

Gligorijevic, Jelena (Yahoo Research)
	Applied Data Science Track~ Understanding Consumer Journey using Attention based Recurrent Neural Networks

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

Goldsberry, Kirk (University of Texas, Austin)
	Applied Data Science Track~ DeepHoops: Evaluating Micro-Actions in Basketball Using Deep Feature Representations of Spatio-Temporal Data

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Gollapudi, Sreenivas (Google Research)
	Applied Data Science Invited Talk~ Welfare Maximization in Online Two-sided Marketplaces

Gong, Neil Zhenqiang (Duke University)
	Applied Data Science Track~ Characterizing and Detecting Malicious Accounts in Privacy-Centric Mobile Social Networks: A Case Study

Gong, Yongshun (JD AI Research & University of Technology Sydney)
	Applied Data Science Track~ Sample Adaptive Multiple Kernel Learning for Failure Prediction of Railway Points

Gong, Yu (Alibaba Group)
	Research Track~ A Minimax Game for Instance based Selective Transfer Learning
	Research Track~ Exact-K Recommendation via Maximal Clique Optimization

Goodrich, Ben (Google Brain)
	Research Track~ Assessing The Factual Accuracy of Generated Text

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

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

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

Gou, Shan (Baidu Research & University of Electronic Science and Technology of China)
	Applied Data Science Track~ A Collaborative Learning Framework to Tag Refinement for Points of Interest

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Govindaraj, Dinesh (Amazon.com)
	Applied Data Science Track~ Whole Page Optimization with Global Constraints

Grabocka, Josif (University of Hildesheim)
	Research Track~ Multi-Relational Classification via Bayesian Ranked Non-Linear Embeddings

Grewal, Elena (Airbnb)
	Applied Data Science Invited Talk~ Seven Years of Data Science at Airbnb

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

Grokhovetskiy, Ruslan (Yandex)
	Applied Data Science Track~ Precipitation Nowcasting with Satellite Imagery

Grossglauser, Matthias (École Polytechnique Fédérale de Lausanne)
	Research Track~ Pairwise Comparisons with Flexible Time-Dynamics

Gu, Bin (JD Finance America Corporation)
	Research Track~ Tackle Balancing Constraint for Incremental Semi-Supervised Support Vector Learning

Gu, Chenjie (DeepMind)
	Applied Data Science Track~ A Generalized Framework for Population Based Training

Gu, Hao (Amazon)
	Applied Data Science Track~ Semantic Product Search

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

Guan, Sheng (Washington State University)
	Research Track~ Attribute-Driven Backbone Discovery

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Guan, Wanxian (Alibaba Group)
	Applied Data Science Track~ Personalized Attraction Enhanced Sponsored Search with Multi-task Learning

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

Guan, Ziyu (Xidian University)
	Research Track~ Exact-K Recommendation via Maximal Clique Optimization
	Research Track~ Riker: Mining Rich Keyword Representations for Interpretable Product Question Answering
	Applied Data Science Track~ IntentGC: A Scalable Graph Convolution Framework Fusing Heterogeneous Information for Recommendation
	Applied Data Science Track~ Personalized Attraction Enhanced Sponsored Search with Multi-task Learning

Guestrin, Carlos (Apple Inc)
	Applied Data Science Track~ Raise to Speak: An Accurate, Low-power Detector for Activating Voice Assistants on Smartwatches
	Applied Data Science Invited Talk~ 4 Perspectives in Human-Centered Machine Learning

Gummadi, Krishna P. (Max Planck Institute for Software Systems)
	Applied Data Science Track~ Two-Sided Fairness for Repeated Matchings in Two-Sided Markets: A Case Study of a Ride-Hailing Platform

Günnemann, Stephan (Technical University of Munich)
	Research Track~ Certifiable Robustness and Robust Training for Graph Convolutional Networks

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

Guo, Jiacheng (Baidu Inc.)
	Applied Data Science Track~ MOBIUS: Towards the Next Generation of Query-Ad Matching in Baidu's Sponsored Search

Guo, Lei (Shandong Normal University)
	Research Track~ Streaming Session-based Recommendation

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

Guo, Ruocheng (Arizona State University)
	Research Track~ Adaptive Unsupervised Feature Selection on Attributed Networks

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

Guo, Weiwei (LinkedIn)
	Tutorial~ Deep Natural Language Processing for Search and Recommender Systems

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

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

Guo, Zhi (Baidu, Inc.)
	Applied Data Science Track~ AiAds: Automated and Intelligent Advertising System for Sponsored Search

Gupchup, Jayant (Microsoft Corporation)
	Applied Data Science Track~ Diagnosing Sample Ratio Mismatch in Online Controlled Experiments: A Taxonomy and Rules of Thumb for Practitioners

Gupta, Pramod (DeepMind)
	Applied Data Science Track~ A Generalized Framework for Population Based Training

Gupta, Rupesh (LinkedIn Corporation)
	Applied Data Science Track~ Internal Promotion Optimization

Gupta, Somit (Microsoft Corporation)
	Applied Data Science Track~ Diagnosing Sample Ratio Mismatch in Online Controlled Experiments: A Taxonomy and Rules of Thumb for Practitioners
	Tutorial~ Challenges, Best Practices and Pitfalls in Evaluating Results of Online Controlled Experiments

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Haas, Kevin (Google)
	Applied Data Science Invited Talk~ Towards ML Engineering with TensorFlow Extended (TFX)

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

Han, Fred X. (University of Alberta)
	Applied Data Science Track~ A Deep Generative Approach to Search Extrapolation and Recommendation

Han, Jiawei (University of Illinois Urbana-Champaign)
	Tutorial~ Constructing and Mining Heterogeneous Information Networks from Massive Text

Han, Peng (King Abdullah University of Science and Technology)
	Research Track~ GCN-MF: Disease-Gene Association Identification By Graph Convolutional Networks and Matrix Factorization

Han, Sungwon (Korea Advanced Institute of Science and Technology)
	Applied Data Science Track~ Learning Sleep Quality from Daily Logs

Han, Xiaotian (Beijing University of Posts and Telecommunications)
	Applied Data Science Track~ Metapath-guided Heterogeneous Graph Neural Network for Intent Recommendation

Han, Zhichao (The Chinese University of Hong Kong)
	Research Track~ Predicting Path Failure In Time-Evolving Graphs

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

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

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

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Harley, Tim (DeepMind)
	Applied Data Science Track~ A Generalized Framework for Population Based Training

Hartvigsen, Thomas (Worcester Polytechnic Institute)
	Research Track~ Adaptive-Halting Policy Network for Early Classification

Hasan, Mohammad Al (Indiana University Purdue University Indianapolis)
	Applied Data Science Track~ Investigate Transitions into Drug Addiction through Text Mining of Reddit Data

He, Jingrui (Arizona State University)
	Research Track~ DEMO-Net: Degree-specific Graph Neural Networks for Node and Graph Classification
	Research Track~ Task-Adversarial Co-Generative Nets
	Tutorial~ Gold Panning from the Mess: Rare Category Exploration, Exposition, Representation, and Interpretation

He, Jingrui (Arizona State University)
	Tutorial~ Optimizing the Wisdom of the Crowd: Inference, Learning, and Teaching

He, Li (JD.com)
	Research Track~ Off-policy Learning for Multiple Loggers

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

He, Qi (LinkedIn)
	Applied Data Science Track~ Social Skill Validation at LinkedIn

He, Qing (Institute of Computing Technology, CAS & University of Chinese Academy of Sciences)
	Research Track~ The Impact of Person-Organization Fit on Talent Management: A Structure-Aware Convolutional Neural Network Approach

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He, Xiangnan (University of Science and Technology of China)
	Research Track~ KGAT: Knowledge Graph Attention Network for Recommendation
	Research Track~ ?Opt: Learn to Regularize Recommender Models in Finer Levels
	Research Track~ Modeling Extreme Events in Time Series Prediction
	Research Track~ Sets2Sets: Learning from Sequential Sets with Neural Networks

He, Xiaofei (Zhejiang University)
	Applied Data Science Track~ IntentGC: A Scalable Graph Convolution Framework Fusing Heterogeneous Information for Recommendation

He, Yancheng (Tencent)
	Applied Data Science Track~ A Deep Generative Approach to Search Extrapolation and Recommendation

He, Zhicheng (Nankai University)
	Research Track~ Learning Network-to-Network Model for Content-rich Network Embedding

Heckerman, David (Amazon)
	Applied Data Science Invited Talk~ Exploiting High Dimensionality in Big Data

Heidari, Hoda (ETH Zürich)
	Applied Data Science Track~ Mathematical Notions vs. Human Perception of Fairness: A Descriptive Approach to Fairness for Machine Learning

Heimann, Mark (University of Michigan Ann Arbor)
	Applied Data Science Track~ Smart Roles: Inferring Professional Roles in Email Networks

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

Henderson, Adam (Etsy)
	Applied Data Science Track~ Understanding the Role of Style in E-commerce Shopping

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Henelius, Andreas (University of Helsinki)
	Research Track~ Significance of Patterns in Data Visualisations

Hibschman, Johann (Google Inc.)
	Applied Data Science Track~ Constructing High Precision Knowledge Bases with Subjective and Factual Attributes

Hidalgo, César (Massachusetts Institute of Technology)
	Research Track~ Sherlock: A Deep Learning Approach to Semantic Data Type Detection

Hoi, Steven C. H. (Singapore Management University & Salesforce Research Asia)
	Applied Data Science Track~ FoodAI: Food Image Recognition via Deep Learning for Smart Food Logging

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

Hong, Liangjie (Etsy, Inc.)
	Applied Data Science Track~ The Identification and Estimation of Direct and Indirect Effects in A/B Tests through Causal Mediation Analysis
	Applied Data Science Track~ Understanding the Role of Style in E-commerce Shopping

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

Hooi, Bryan (National University of Singapore)
	Research Track~ Fast and Accurate Anomaly Detection in Dynamic Graphs with a Two-Pronged Approach

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

Hossain, H M Sajjad (University of Maryland Baltimore County)
	Applied Data Science Track~ Active Deep Learning for Activity Recognition with Context Aware Annotator Selection

Hou, Yifan (The Chinese University of Hong Kong)
	Research Track~ A Representation Learning Framework for Property Graphs

Houle, Michael E. (National Institute of Informatics)
	Research Track~ Improving the Quality of Explanations with Local Embedding Perturbations

Hsieh, Cho-Jui (University of California, Los Angeles)
	Research Track~ Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks

Hsu, Cheng (National Cheng Kung University)
	Applied Data Science Track~ Learning Sleep Quality from Daily Logs

Hu, Binbin (Beijing University of Posts and Telecommunications & Ant Financial Services Group)
	Research Track~ Adversarial Learning on Heterogeneous Information Networks

Hu, Diane (Etsy)
	Applied Data Science Track~ Understanding the Role of Style in E-commerce Shopping

Hu, Haoji (University of Minnesota, Twin Cities)
	Research Track~ Sets2Sets: Learning from Sequential Sets with Neural Networks

Hu, Ke (Alibaba Group)
	Applied Data Science Track~ AccuAir: Winning Solution to Air Quality Prediction for KDD Cup 2020

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Hu, Kevin (Massachusetts Institute of Technology)
	Research Track~ Sherlock: A Deep Learning Approach to Semantic Data Type Detection

Hu, Linmei (Beijing University of Posts and Telecommunications)
	Applied Data Science Track~ Metapath-guided Heterogeneous Graph Neural Network for Intent Recommendation

Hu, Renjun (Business Intelligence Lab, Baidu Research)
	Applied Data Science Track~ A Collaborative Learning Framework to Tag Refinement for Points of Interest

Hu, Wenbin (Wuhan University & Shenzhen Research Institute, Wuhan University)
	Research Track~ Link Prediction with Signed Latent Factors in Signed Social Networks

Hu, Xia (Texas A&M University)
	Research Track~ Coupled Variational Recurrent Collaborative Filtering
	Research Track~ Graph Recurrent Networks With Attributed Random Walks
	Research Track~ Is a Single Vector Enough? Exploring Node Polysemy for Network Embedding
	Applied Data Science Track~ Auto-Keras: An Efficient Neural Architecture Search System

Hu, Yaochen (University of Alberta)
	Applied Data Science Track~ FDML: A Collaborative Machine Learning Framework for Distributed Features

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

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

Huang, Chao (University of Notre Dame, JD Digits)
	Research Track~ Heterogeneous Graph Neural Network
	Applied Data Science Track~ Online Purchase Prediction via Multi-Scale Modeling of Behavior Dynamics

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

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Huang, Dou (The University of Tokyo)
	Applied Data Science Track~ DeepUrbanEvent: A System for Predicting Citywide Crowd Dynamics at Big Events

Huang, Heng (University of Pittsburgh & JD Finance America Corporation)
	Research Track~ Conditional Random Field Enhanced Graph Convolutional Neural Networks
	Research Track~ ProGAN: Network Embedding via Proximity Generative Adversarial Network
	Research Track~ Tackle Balancing Constraint for Incremental Semi-Supervised Support Vector Learning
	Applied Data Science Track~ Multi-Horizon Time Series Forecasting with Temporal Attention Learning

Huang, Jianqiang (Peking University)
	Applied Data Science Track~ AccuAir: Winning Solution to Air Quality Prediction for KDD Cup 2019
	Applied Data Science Track~ NPA: Neural News Recommendation with Personalized Attention

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

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

Huang, Linpeng (Shanghai Jiao Tong University)
	Research Track~ Incorporating Interpretability into Latent Factor Models via Fast Influence Analysis

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

Huang, Sheng-Jun (Nanjing University of Aeronautics and Astronautics)
	Research Track~ Learning Class-Conditional GANs with Active Sampling

Huang, Silu (University of Illinois, Urbana-Champaign)
	Research Track~ Contextual Fact Ranking and Its Applications in Table Synthesis and Compression

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Huang, Xiao (Texas A&M University)
	Research Track~ Graph Recurrent Networks With Attributed Random Walks
	Tutorial~ Learning From Networks: Algorithms, Theory, and Applications

Huang, Yalou (Nankai University)
	Research Track~ Learning Network-to-Network Model for Content-rich Network Embedding

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

Huang, Yungui (Abigail Wexner Research Institute at Nationwide Children’s Hospital)
	Research Track~ SurfCon: Synonym Discovery on Privacy-Aware Clinical Data

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

Huang, Zi (The University of Queensland)
	Research Track~ Enhancing Collaborative Filtering with Generative Augmentation

Hughes, J. Weston (University of California, Berkeley)
	Applied Data Science Track~ Generating Better Search Engine Text Advertisements with Deep Reinforcement Learning

Hulsebos, Madelon (Massachusetts Institute of Technology)
	Research Track~ Sherlock: A Deep Learning Approach to Semantic Data Type Detection

Huo, Siyu (IBM Research)
	Research Track~ Efficient Global String Kernel with Random Features: Beyond Counting Substructures

Hutchinson, Ben (Google)
	Tutorial~ Fairness-Aware Machine Learning: Practical Challenges and Lessons Learned

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Hwang, Jessica (Stanford University)
	Applied Data Science Track~ Improving Subseasonal Forecasting in the Western U.S. with Machine Learning

Hwang, Seong Jae (University of Wisconsin-Madison)
	Applied Data Science Track~ Large-Scale Training Framework for Video Annotation

Im, Jinbae (NCSOFT Co.)
	Research Track~ MeLU: Meta-Learned User Preference Estimator for Cold-Start Recommendation

Inaba, Sho (University of Massachusetts Boston)
	Research Track~ A Free Energy Based Approach for Distance Metric Learning

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

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

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

Ivashkin, Vladimir (Yandex)
	Applied Data Science Track~ Precipitation Nowcasting with Satellite Imagery

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

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Iyatomi, Hitoshi (Hosei University)
	Applied Data Science Track~ Conversion Prediction Using Multi-task Conditional Attention Networks to Support the Creation of Effective Ad Creatives

Iyengar, Garud (Columbia University)
	Research Track~ Sequential Anomaly Detection using Inverse Reinforcement Learning

Iyengar, Srinivasan (Microsoft Research, Bangalore)
	Applied Data Science Track~ DeepRoof: A Data-driven Approach For Solar Potential Estimation Using Rooftop Imagery

Jaderberg, Max (DeepMind)
	Applied Data Science Track~ A Generalized Framework for Population Based Training

Jang, Seongwon (NCSOFT Co.)
	Research Track~ MeLU: Meta-Learned User Preference Estimator for Cold-Start Recommendation

Jankovic, Filip (Evidation Health, Inc.)
	Applied Data Science Track~ Developing Measures of Cognitive Impairment in the Real World from Consumer-Grade Multimodal Sensor Streams

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

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

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Jensen, Christian S. (Aalborg University)
	Research Track~ Effective and Efficient Reuse of Past Travel Behavior for Route Recommendation

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

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

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

Ji, Shouling (Zhejiang University)
	Research Track~ Efficient Global String Kernel with Random Features: Beyond Counting Substructures

Ji, Shuiwang (Texas A&M University)
	Research Track~ Graph Representation Learning via Hard and Channel-Wise Attention Networks

Jia, Junteng (Cornell University)
	Research Track~ Graph-based Semi-Supervised & Active Learning for Edge Flows

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

Jia, Xiaowei (University of Minnesota & Adobe Research)
	Research Track~ Towards Robust and Discriminative Sequential Data Learning: When and How to Perform Adversarial Training?

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Jia, Yunzhe (University of Melbourne)
	Research Track~ Improving the Quality of Explanations with Local Embedding Perturbations

Jiang, Airong (Baidu Research & National Engineering Laboratory of Deep Learning Technology and Application)
	Applied Data Science Track~ A Collaborative Learning Framework to Tag Refinement for Points of Interest

Jiang, Hao (Twitter)
	Applied Data Science Track~ Understanding the Role of Style in E-commerce Shopping

Jiang, Lei (Beijing Jiaotong University)
	Applied Data Science Track~ LightNet: A Dual Spatiotemporal Encoder Network Model for Lightning Prediction

Jiang, Meng (University of Notre Dame)
	Research Track~ The Role of "Condition": A Novel Scientific Knowledge Graph Representation and Construction Model
	Research Track~ TUBE: Embedding Behavior Outcomes for Predicting Success

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

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

Jiang, Renhe (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

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Jiang, Tianwen (University of Notre Dame & Harbin Institute of Technology)
	Research Track~ The Role of "Condition": A Novel Scientific Knowledge Graph Representation and Construction Model
	Research Track~ TUBE: Embedding Behavior Outcomes for Predicting Success

Jiang, Yuan (Nanjing University)
	Research Track~ Adaptive Deep Models for Incremental Learning: Considering Capacity Scalability and Sustainability
	Research Track~ Learning from Incomplete and Inaccurate Supervision

Jiang, Zhe (University of Alabama)
	Research Track~ Hidden Markov Contour Tree: A Spatial Structured Model for Hydrological Applications

Jin, Depeng (Tsinghua University)
	Research Track~ State-Sharing Sparse Hidden Markov Models for Personalized Sequences

Jin, Di (University of Michigan)
	Research Track~ Latent Network Summarization: Bridging Network Embedding and Summarization
	Applied Data Science Track~ Smart Roles: Inferring Professional Roles in Email Networks

Jin, Haifeng (Texas A&M University)
	Applied Data Science Track~ Auto-Keras: An Efficient Neural Architecture Search System

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Jin, Hongxia (Samsung Research America)
	Research Track~ An Visual Dialog Augmented Interactive Recommender System

Jin, Rong (Alibaba Group)
	Applied Data Science Track~ Robust Gaussian Process Regression for Real-Time High Precision GPS Signal Enhancement

Jing, Lin (Xidian University)
	Applied Data Science Track~ UrbanFM: Inferring Fine-Grained Urban Flows

Ju, Ce (Intelligent Driving Group, Baidu Inc.)
	Research Track~ Effective and Efficient Sports Play Retrieval with Deep Representation Learning

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

Jung, Okchul (Korea Aerospace Research Institute (KARI))
	Applied Data Science Track~ Detecting Anomalies in Space using Multivariate Convolutional LSTM with Mixtures of Probabilistic PCA

Kalnis, Panos (King Abdullah University of Science and Technology)
	Research Track~ GCN-MF: Disease-Gene Association Identification By Graph Convolutional Networks and Matrix Factorization

Kalpathy-Cramer, Jayashree (Massachusetts General Hospital)
	Applied Data Science Track~ A Severity Score for Retinopathy of Prematurity

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Kalra, Achir (Forbes Media LLC)
	Applied Data Science Track~ Reserve Price Failure Rate Prediction with Header Bidding in Display Advertising

Kamali, Shahab (Google Research)
	Applied Data Science Track~ Randomized Experimental Design via Geographic Clustering

Kan, Andrey (Amazon)
	Research Track~ Estimating Node Importance in Knowledge Graphs Using Graph Neural Networks

Kang, Peng (Northwestern University)
	Research Track~ Hierarchical Gating Networks for Sequential Recommendation

Kapoor, Amol (Google Research)
	Applied Data Science Track~ Nostalgin: Extracting 3D City Models from Historical Image Data

Karasuyama, Masayuki (Nagoya Institute of Technology & National Institute for Material Science & Japan Science and Technology Agency)
	Research Track~ Learning Interpretable Metric between Graphs: Convex Formulation and Computation with Graph Mining

Karras, Panagiotis (Aarhus University)
	Research Track~ Figuring out the User in a Few Steps: Bayesian Multifidelity Active Search with Cokriging

Katsiapis, Konstantinos (Google)
	Applied Data Science Invited Talk~ Towards ML Engineering with TensorFlow Extended (TFX)

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

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

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Ke, Guolin (Microsoft Research)
	Research Track~ DeepGBM: A Deep Learning Framework Distilled by GBDT for Online Prediction Tasks

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

Kenthapadi, Krishnaram (LinkedIn Corporation)
	Applied Data Science Track~ Fairness-Aware Ranking in Search & Recommendation Systems with Application to LinkedIn Talent Search
	Tutorial~ Explainable AI in Industry
	Tutorial~ Fairness-Aware Machine Learning: Practical Challenges and Lessons Learned

Keogh, Eamonn (University of California, Riverside)
	Applied Data Science Track~ Online Amnestic DTW to allow Real-Time Golden Batch Monitoring

Kıcıman, Emre (Microsoft)
	Tutorial~ Fairness-Aware Machine Learning: Practical Challenges and Lessons Learned

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

Killian, Jackson A. (University of Southern California)
	Applied Data Science Track~ Learning to Prescribe Interventions for Tuberculosis Patients Using Digital Adherence Data

Kim, Dae Won (Cornell University)
	Research Track~ OBOE: Collaborative Filtering for AutoML Model Selection

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

Kim, Sungchul (Adobe Research)
	Research Track~ Latent Network Summarization: Bridging Network Embedding and Summarization
	Research Track~ Towards Robust and Discriminative Sequential Data Learning: When and How to Perform Adversarial Training?

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

Kirsch, Christina (Sydney Trains-Operational Technology)
	Applied Data Science Track~ Sample Adaptive Multiple Kernel Learning for Failure Prediction of Railway Points

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

Kitada, Shunsuke (Hosei University)
	Applied Data Science Track~ Conversion Prediction Using Multi-task Conditional Attention Networks to Support the Creation of Effective Ad Creatives

Kiveris, Raimondas (Google Research)
	Applied Data Science Track~ Nostalgin: Extracting 3D City Models from Historical Image Data

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

Klein, Paul (Siemens Healthineers)
	Research Track~ Training and Meta-Training Binary Neural Networks with Quantum Computing

Klimov, Denis (Ben-Gurion University)
	Applied Data Science Track~ Temporal Probabilistic Profiles for Sepsis Prediction in the ICU

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Klyuchnikov, Nikita (Skoltech)
	Research Track~ Figuring out the User in a Few Steps: Bayesian Multifidelity Active Search with Cokriging

Kobren, Ari (University of Massachusetts, Amherst)
	Research Track~ Paper Matching with Local Fairness Constraints
	Research Track~ Scalable Hierarchical Clustering with Tree Grafting
	Applied Data Science Track~ Constructing High Precision Knowledge Bases with Subjective and Factual Attributes

Koch, Paul (Microsoft Research)
	Research Track~ Axiomatic Interpretability for Multiclass Additive Models

Koh, Eunyee (Adobe Research)
	Research Track~ Latent Network Summarization: Bridging Network Embedding and Summarization

Kolbeinsson, Arinbjörn (Imperial College London)
	Applied Data Science Track~ Dynamic Pricing for Airline Ancillaries with Customer Context

Komiyama, Junpei (University of Tokyo)
	Research Track~ Scaling Multi-Armed Bandit Algorithms

Kong, Xiangnan (Worcester Polytechnic Institute)
	Research Track~ Adaptive-Halting Policy Network for Early Classification

Koo, Bonsoo (Monash University)
	Research Track~ Regularized Regression for Hierarchical Forecasting Without Unbiasedness Conditions

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

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

Kourtis, Lampros (Evidation Health, Inc.)
	Applied Data Science Track~ Developing Measures of Cognitive Impairment in the Real World from Consumer-Grade Multimodal Sensor Streams

Koutra, Danai (University of Michigan)
	Research Track~ GroupINN: Grouping-based Interpretable Neural Network for Classification of Limited, Noisy Brain Data
	Research Track~ Latent Network Summarization: Bridging Network Embedding and Summarization
	Applied Data Science Track~ Smart Roles: Inferring Professional Roles in Email Networks

Koutrika, Georgia (Athena Research and Innovation Center)
	Research Track~ Figuring out the User in a Few Steps: Bayesian Multifidelity Active Search with Cokriging

Kovalerchuk, Boris (Central Washington University)
	Tutorial~ Interpretable Knowledge Discovery Reinforced by Visual Methods

Koyama, Masanori (Preferred Networks, Inc.)
	Applied Data Science Track~ Optuna: A Next-generation Hyperparameter Optimization Framework

Kraska, Tim (Massachusetts Institute of Technology)
	Research Track~ Sherlock: A Deep Learning Approach to Semantic Data Type Detection

Kraus, Mathias (ETH Zurich)
	Applied Data Science Track~ Personalized Purchase Prediction of Market Baskets with Wasserstein-Based Sequence Matching

Krause, Andreas (ETH Zürich)
	Applied Data Science Track~ Mathematical Notions vs. Human Perception of Fairness: A Descriptive Approach to Fairness for Machine Learning

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Krishnamurthy, Akshay (Microsoft Research)
	Research Track~ Scalable Hierarchical Clustering with Tree Grafting

Kristof, Victor (École Polytechnique Fédérale de Lausanne)
	Research Track~ Pairwise Comparisons with Flexible Time-Dynamics

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

Kuang, Kun (Tsinghua University)
	Research Track~ Focused Context Balancing for Robust Offline Policy Evaluation

Kulkarni, Rahul V. (University of Massachusetts Boston)
	Research Track~ A Free Energy Based Approach for Distance Metric Learning

Kumar, Ravi (Google Research)
	Research Track~ Clustering without Over-Representation
	Applied Data Science Track~ Hard to Park? Estimating Parking Difficulty at Scale

Kumar, Srijan (Stanford University & Georgia Institute of Technology)
	Research Track~ Predicting Dynamic Embedding Trajectory in Temporal Interaction Networks

Kumar, Vipin (University of Minnesota)
	Research Track~ Towards Robust and Discriminative Sequential Data Learning: When and How to Perform Adversarial Training?

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

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

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Lachance, Jean-Christophe (Université de Sherbrooke)
	Applied Data Science Track~ Estimating Cellular Goals from High-Dimensional Biological Data

Lahaie, Sébastien (Google Research)
	Research Track~ Testing Dynamic Incentive Compatibility in Display Ad Auctions

Lai, Jian-Huang (Sun Yat-sen University)
	Research Track~ EdMot: An Edge Enhancement Approach for Motif-aware Community Detection

Lai, Kunfeng (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

Lakshman, Vihan (Amazon)
	Applied Data Science Track~ Semantic Product Search

Lamba, Hemank (Carnegie Mellon University)
	Research Track~ Modeling Dwell Time Engagement on Visual Multimedia

Langmore, Ian (Google Inc.)
	Applied Data Science Track~ Constructing High Precision Knowledge Bases with Subjective and Factual Attributes

Larco, Hunter (Google Research)
	Applied Data Science Track~ Nostalgin: Extracting 3D City Models from Historical Image Data

LaRock, Timothy (Northeastern University)
	Tutorial~ Incompleteness in Networks: Biases, Skewed Results, and Some Solutions

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

Le, Ran (Peking University)
	Research Track~ Interview Choice Reveals Your Preference on the Market: To Improve Job-Resume Matching through Profiling Memories

Lebedev, Vadim (Yandex)
	Applied Data Science Track~ Precipitation Nowcasting with Satellite Imagery

Leckie, Christopher (University of Melbourne)
	Research Track~ Improving the Quality of Explanations with Local Embedding Perturbations

Lee, Benjamin N. (Google)
	Applied Data Science Track~ Gmail Smart Compose: Real-Time Assisted Writing

Lee, Dongwon (Penn State University)
	Research Track~ dEFEND: Explainable Fake News Detection

Lee, Hoyeop (NCSOFT Co.)
	Research Track~ MeLU: Meta-Learned User Preference Estimator for Cold-Start Recommendation

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

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Lee, Myeong Shin (Korea Aerospace Research Institute (KARI))
	Applied Data Science Track~ Detecting Anomalies in Space using Multivariate Convolutional LSTM with Mixtures of Probabilistic PCA

Lee, Peter (Microsoft Healthcare)
	Keynote Talk~ The Unreasonable Effectiveness, and Difficulty, of Data in Healthcare

Lee, Sang Won (Kyungpook National University Chilgok Hospital)
	Applied Data Science Track~ Learning Sleep Quality from Daily Logs

Lee, Sangyup (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

Lee, Stephen (University of Massachusetts, Amherst)
	Applied Data Science Track~ DeepRoof: A Data-driven Approach For Solar Potential Estimation Using Rooftop Imagery

Lee, Wei (Trove AI)
	Applied Data Science Track~ Smart Roles: Inferring Professional Roles in Email Networks

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

Lehman, Li-wei H. (Massachusetts Institute of Technology)
	Research Track~ Retaining Privileged Information for Multi-Task Learning

Leskovec, Jure (Stanford University)
	Research Track~ Knowledge-aware Graph Neural Networks with Label Smoothness Regularization for Recommender Systems
	Research Track~ Predicting Dynamic Embedding Trajectory in Temporal Interaction Networks

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Li, Ang (DeepMind)
	Applied Data Science Track~ A Generalized Framework for Population Based Training

Li, Bin (Fudan University)
	Research Track~ NodeSketch: Highly-Efficient Graph Embeddings via Recursive Sketching

Li, Boyang (Northeastern University)
	Research Track~ Three-Dimensional Stable Matching Problem for Spatial Crowdsourcing Platforms

Li, Chang (UBTECH Sydney AI Centre, SCS, University of Sydney & Capital Markets CRC, Australia)
	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

Li, Changji (The Chinese University of Hong Kong)
	Research Track~ A Representation Learning Framework for Property Graphs

Li, Chao (Walmart Labs)
	Applied Data Science Track~ Anomaly Detection for an E-commerce Pricing System

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

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

Li, Cheng-Te (National Cheng Kung University)
	Applied Data Science Track~ Learning Sleep Quality from Daily Logs

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Li, Fei (University of Massachusetts, Lowell)
	Applied Data Science Track~ Naranjo Question Answering using End-to-End Multi-task Learning Model

Li, Fengjie Alex (Ancestry)
	Applied Data Science Track~ Ranking in Genealogy: Search Results Fusion at Ancestry

Li, Hao (Alibaba Group)
	Applied Data Science Track~ Robust Gaussian Process Regression for Real-Time High Precision GPS Signal Enhancement

Li, Haoyang (Tsinghua University)
	Research Track~ Fates of Microscopic Social Ecosystems: Keep Alive or Dead?

Li, Jia (The Chinese University of Hong Kong)
	Research Track~ Predicting Path Failure In Time-Evolving Graphs

Li, Jing (Wuhan University)
	Research Track~ DAML: Dual Attention Mutual Learning between Ratings and Reviews for Item Recommendation

Li, Jundong (Arizona State University)
	Research Track~ Adaptive Unsupervised Feature Selection on Attributed Networks
	Tutorial~ Learning From Networks: Algorithms, Theory, and Applications

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Li, Keqian (University of California, Santa Barbara)
	Research Track~ Mining Algorithm Roadmap in Scientific Publications

Li, Lei (Bytedance AI Lab)
	Applied Data Science Track~ Uncovering the Co-driven Mechanism of Social and Content Links in User Churn Phenomena

Li, Li (Southwest University)
	Research Track~ Adaptive Graph Guided Disambiguation for Partial Label Learning
	Applied Data Science Track~ Deep Spatio-Temporal Neural Networks for Click-Through Rate Prediction

Li, Liangda (Yahoo! Research)
	Tutorial~ Modeling and Applications for Temporal Point Processes

Li, Na (Nankai University)
	Research Track~ Learning Network-to-Network Model for Content-rich Network Embedding

Li, Pan (University of Illinois at Urbana - Champaign & Google Inc.)
	Applied Data Science Track~ Combining Decision Trees and Neural Networks for Learning-to-Rank in Personal Search

Li, Pei-Zhen (Sun Yat-sen University)
	Research Track~ EdMot: An Edge Enhancement Approach for Motif-aware Community Detection

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Li, Ping (Baidu Research)
	Research Track~ Hierarchical Multi-Task Word Embedding Learning for Synonym Prediction
	Applied Data Science Track~ MOBIUS: Towards the Next Generation of Query-Ad Matching in Baidu's Sponsored Search

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

Li, Qingyang (AI Labs, Didi Chuxing)
	Research Track~ Environment Reconstruction with Hidden Confounders for Reinforcement Learning based Recommendation

Li, Qingyong (Beijing Jiaotong University)
	Applied Data Science Track~ LightNet: A Dual Spatiotemporal Encoder Network Model for Lightning Prediction

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

Li, Sheng (University of Georgia)
	Research Track~ Log2Intent: Towards Interpretable User Modeling via Recurrent Semantics Memory Unit
	Research Track~ Towards Robust and Discriminative Sequential Data Learning: When and How to Perform Adversarial Training?

Li, Tianrui (Southwest Jiaotong University)
	Applied Data Science Track~ Deep Uncertainty Quantification: A Machine Learning Approach for Weather Forecasting

Li, Wenjie (Hong Kong Polytechnic University)
	Research Track~ Knowledge-aware Graph Neural Networks with Label Smoothness Regularization for Recommender Systems

Li, Xiaolin (Nanjing University)
	Research Track~ Adversarial Substructured Representation Learning for Mobile User Profiling
	Research Track~ Automating Feature Subspace Exploration via Multi-Agent Reinforcement Learning
	Research Track~ Unifying Inter-region Autocorrelation and Intra-region Structures for Spatial Embedding via Collective Adversarial Learning

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

Li, Xue (Microsoft)
	Applied Data Science Track~ AccuAir: Winning Solution to Air Quality Prediction for KDD Cup 2021

Li, Xuelong (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

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

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

Li, Yang (Google Research)
	Research Track~ Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks

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

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

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Li, Yexin (Hong Kong University of Science and Technology)
	Research Track~ Efficient and Effective Express via Contextual Cooperative Reinforcement Learning

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

Li, Ying (Baidu Inc.)
	Applied Data Science Track~ A Collaborative Learning Framework to Tag Refinement for Points of Interest

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

Li, Yong (Tsinghua University)
	Research Track~ ?Opt: Learn to Regularize Recommender Models in Finer Levels
	Research Track~ State-Sharing Sparse Hidden Markov Models for Personalized Sequences

Li, Yongliang (Alibaba Group)
	Applied Data Science Track~ Metapath-guided Heterogeneous Graph Neural Network for Intent Recommendation

Li, Yuchen (Singapore Management University)
	Research Track~ Coresets for Minimum Enclosing Balls over Sliding Windows
	Research Track~ Optimizing Impression Counts for Outdoor Advertising

Li, Yuening (Texas A&M University)
	Research Track~ Graph Recurrent Networks With Attributed Random Walks
	Research Track~ Is a Single Vector Enough? Exploring Node Polysemy for Network Embedding

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

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

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

Li, Zhige (Shanghai Jiao Tong University)
	Research Track~ Factorization Bandits for Online Influence Maximization
	Research Track~ Individualized Indicator for All: Stock-wise Technical Indicator Optimization with Stock Embedding

Liakhovich, Olga (Microsoft)
	Applied Data Science Invited Talk~ Preventing Rhino Poaching through Machine Learning

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

Liang, Huai-Jen (Google Research)
	Applied Data Science Track~ Hard to Park? Estimating Parking Difficulty at Scale

Liang, Yuxuan (Xidian University)
	Research Track~ Urban Traffic Prediction from Spatio-Temporal Data Using Deep Meta Learning
	Applied Data Science Track~ UrbanFM: Inferring Fine-Grained Urban Flows

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Liao, Wei-keng (Northwestern University)
	Applied Data Science Track~ IRNet: A General Purpose Deep Residual Regression Framework for Materials Discovery

Lijffijt, Jefrey (Ghent University)
	Research Track~ Contrastive Antichains in Hierarchies

Lim, Ee-Peng (Singapore Management University)
	Applied Data Science Track~ FoodAI: Food Image Recognition via Deep Learning for Smart Food Logging

Lin, Hsuan-Tien (National Taiwan University)
	Tutorial~ Advances in Cost-sensitive Multiclass and Multilabel Classification

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

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

Lin, Junyang (Peking University & Alibaba Group)
	Applied Data Science Track~ Towards Knowledge-Based Personalized Product Description Generation in E-commerce

Lin, Leyu (WeiXin Group, Tencent Inc.)
	Applied Data Science Track~ Real-time Attention Based Look-alike Model for Recommender System

Lin, Ming (Alibaba Group)
	Applied Data Science Track~ Robust Gaussian Process Regression for Real-Time High Precision GPS Signal Enhancement

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Lin, Simon (Abigail Wexner Research Institute at Nationwide Children’s Hospital)
	Research Track~ SurfCon: Synonym Discovery on Privacy-Aware Clinical Data

Lin, Tianyang (Beijing Jiaotong University)
	Applied Data Science Track~ LightNet: A Dual Spatiotemporal Encoder Network Model for Lightning Prediction

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

Lin, Yishi (Tencent)
	Research Track~ Fates of Microscopic Social Ecosystems: Keep Alive or Dead?

Liu, Bang (University of Alberta)
	Applied Data Science Track~ A User-Centered Concept Mining System for Query and Document Understanding at Tencent

Liu, Chang (Citadel Securities)
	Applied Data Science Track~ Characterizing and Detecting Malicious Accounts in Privacy-Centric Mobile Social Networks: A Case Study

Liu, Chenghao (Singapore Management University)
	Research Track~ Adaptive Unsupervised Feature Selection on Attributed Networks
	Research Track~ Social Recommendation with Optimal Limited Attention

Liu, Chuanren (University of Tennessee)
	Research Track~ Exploiting Cognitive Structure for Adaptive Learning

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

Liu, Donghua (Wuhan University)
	Research Track~ DAML: Dual Attention Mutual Learning between Ratings and Reviews for Item Recommendation

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

Liu, Hao (Baidu Research)
	Applied Data Science Track~ Hydra: A Personalized and Context-Aware Multi-Modal Transportation Recommendation System

Liu, Hongmin (Henan Polytechnic University)
	Applied Data Science Track~ Personalized Attraction Enhanced Sponsored Search with Multi-task Learning

Liu, Huan (Arizona State University)
	Research Track~ Adaptive Unsupervised Feature Selection on Attributed Networks
	Research Track~ dEFEND: Explainable Fake News Detection
	Tutorial~ Fake News Research: Theories, Detection Strategies, and Open Problems
	Tutorial~ Learning From Networks: Algorithms, Theory, and Applications

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

Liu, Jie (Nankai University)
	Research Track~ Learning Network-to-Network Model for Content-rich Network Embedding

Liu, Kunpeng (University of Central Florida)
	Research Track~ Automating Feature Subspace Exploration via Multi-Agent Reinforcement Learning

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Liu, Liyuan (University of Illinois Urbana-Champaign)
	Tutorial~ Constructing and Mining Heterogeneous Information Networks from Massive Text

Liu, Meng (Shandong University)
	Research Track~ KGAT: Knowledge Graph Attention Network for Recommendation

Liu, Mengyang (Tsinghua University)
	Research Track~ Investigating Cognitive Effects in Session-level Search User Satisfaction

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

Liu, Peter J. (Google Brain)
	Research Track~ Assessing The Factual Accuracy of Generated Text

Liu, Qi (University of Science and Technology of China)
	Research Track~ Exploiting Cognitive Structure for Adaptive Learning
	Research Track~ MCNE: An End-to-End Framework for Learning Multiple Conditional Network Representations of Social Network
	Research Track~ QuesNet: A Unified Representation for Heterogeneous Test Questions

Liu, Qingwen (Alibaba Group)
	Research Track~ Exact-K Recommendation via Maximal Clique Optimization

Liu, Rong (Stevens Institute of Technology)
	Applied Data Science Track~ Robust Anomaly Detection for Multivariate Time Series through Stochastic Recurrent Neural Network

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Liu, Rui (Dartmouth College)
	Applied Data Science Track~ Using Twitter to Predict When Vulnerabilities will be Exploited

Liu, Sijia (IBM Research)
	Tutorial~ Recent Progress in Zeroth Order Optimization and Its Applications to Adversarial Robustness in Data Mining and Machine Learning

Liu, Tie-Yan (Microsoft Research)
	Research Track~ DeepGBM: A Deep Learning Framework Distilled by GBDT for Online Prediction Tasks
	Research Track~ Individualized Indicator for All: Stock-wise Technical Indicator Optimization with Stock Embedding
	Applied Data Science Track~ Investment Behaviors Can Tell What Inside: Exploring Stock Intrinsic Properties for Stock Trend Prediction

Liu, Ting (Harbin Institute of Technology)
	Research Track~ The Role of "Condition": A Novel Scientific Knowledge Graph Representation and Construction Model

Liu, Tracy (Tsinghua University)
	Applied Data Science Track~ Infer Implicit Contexts in Real-time Online-to-Offline Recommendation

Liu, Weidong (Tsinghua University)
	Applied Data Science Track~ Reinforcement Learning to Optimize Long-term User Engagement in Recommender Systems

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

Liu, Xuanqing (University of California, Los Angeles & Google Research)
	Research Track~ Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks

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Liu, Xue (McGill University)
	Research Track~ Hierarchical Gating Networks for Sequential Recommendation

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

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

Liu, Ye (National University of Singapore)
	Applied Data Science Track~ UrbanFM: Inferring Fine-Grained Urban Flows

Liu, Yihao (Bytedance AI Lab)
	Applied Data Science Track~ Uncovering the Co-driven Mechanism of Social and Content Links in User Churn Phenomena
	Research Track~ Investigating Cognitive Effects in Session-level Search User Satisfaction

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

Liu, Yong (Alibaba-NTU Singapore Joint Research Institute, Nanyang Technological University)
	Research Track~ GCN-MF: Disease-Gene Association Identification By Graph Convolutional Networks and Matrix Factorization

Liu, Yozen (University of Southern California)
	Applied Data Science Track~ Characterizing and Forecasting User Engagement with In-App Action Graph: A Case Study of Snapchat

Liu, Yu (Pinterest)
	Applied Data Science Track~ PinText: A Multitask Text Embedding System in Pinterest

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Liu, Yuchao (Microsoft Corporation)
	Research Track~ A Multiscale Scan Statistic for Adaptive Submatrix Localization

Liu, Yudan (WeiXin Group, Tencent Inc.)
	Applied Data Science Track~ Real-time Attention Based Look-alike Model for Recommender System

Liu, Yumin (Northeastern University)
	Applied Data Science Track~ Nonparametric Mixture of Sparse Regressions on Spatio-Temporal Data -- An Application to Climate Prediction

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

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

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

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

Loeliger, Hans-Andrea (ETH Zürich)
	Applied Data Science Track~ Context by Proxy: Identifying Contextual Anomalies Using an Output Proxy

Long, Bo (LinkedIn)
	Tutorial~ Deep Natural Language Processing for Search and Recommender Systems

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

Lou, Jian-Guang (Microsoft Research)
	Research Track~ ?Opt: Learn to Regularize Recommender Models in Finer Levels

Lou, Yin (Ant Financial)
	Research Track~ Axiomatic Interpretability for Multiclass Additive Models

Lu, Chang-Tien (Virginia Tech)
	Tutorial~ Spatio-temporal Event Forecasting and Precursor Identification

Lu, Jie (University of Technology Sydney)
	Applied Data Science Track~ Deep Uncertainty Quantification: A Machine Learning Approach for Weather Forecasting

Lu, John (University of California, Irvine)
	Applied Data Science Track~ Investigate Transitions into Drug Addiction through Text Mining of Reddit Data

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

Lu, Xinjiang (Baidu Research)
	Applied Data Science Track~ Hydra: A Personalized and Context-Aware Multi-Modal Transportation Recommendation System

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

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

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Lui, John C.S. (The Chinese University of Hong Kong)
	Research Track~ A Memory-Efficient Sketch Method for Estimating High Similarities in Streaming Sets

Luo, Huaishao (Southwest Jiaotong University)
	Applied Data Science Track~ Deep Uncertainty Quantification: A Machine Learning Approach for Weather Forecasting

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

Luo, Zhipeng (DeepBlue Technology)
	Applied Data Science Track~ AccuAir: Winning Solution to Air Quality Prediction for KDD Cup 2018

Lv, Weifeng (Beihang University)
	Research Track~ Multiple Relational Attention Network for Multi-task Learning

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

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