KDD ‘17- Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Full Citation in the ACM Digital Library

SESSION: KDD 2017 Keynote Talks

What’s Fair?

• Cynthia Dwork

The Future of Data Integration

• Renée J. Miller

Three Principles of Data Science: Predictability, Stability and Computability

• Bin Yu

SESSION: KDD 2017 Applied Invited Talks

Foreword to the Applied Data Science: Invited Talks Track at KDD-2017

• Usama M. Fayyad
• Evangelos Simoudis
• Ashok Srivastava

More than the Sum of its Parts: Building Domino Data Lab

• Eduardo Ariño de la Rubia

Mining Big Data in NeuroGenetics to Understand Muscular Dystrophy

• Andy Berglund

Industrial Machine Learning

• Josh Bloom

Behavior Informatics to Discover Behavior Insight for Active and Tailored Client Management

• Longbing Cao

It Takes More than Math and Engineering to Hit the Bullseye with Data

• Paritosh Desai

Planning and Learning under Uncertainty: Theory and Practice

• Jonathan P. How

Big Data in Climate: Opportunities and Challenges for Machine Learning

• Anuj Karpatne
• Vipin Kumar

Addressing Challenges with Big Data for Media Measurement

• Mainak Mazumdar

Machine Learning Software in Practice: Quo Vadis?

• Szilárd Pafka

Designing AI at Scale to Power Everyday Life

• Rajesh Parekh

Spaceborne Data Enters the Mainstream

• David Potere

PANEL SESSION: KDD 2017 Panels

Benchmarks and Process Management in Data Science: Will We Ever Get Over the Mess?

• Usama M. Fayyad
• Arno Candel
• Eduardo Ariño de la Rubia
• Szilárd Pafka
• Anthony Chong
• Jeong-Yoon Lee

The Future of Artificially Intelligent Assistants

• Muthu Muthukrishnan
• Andrew Tomkins
• Larry Heck
• Alborz Geramifard
• Deepak Agarwal

SESSION: KDD 2017 Research Papers (Oral Papers)

Learning Certifiably Optimal Rule Lists

• Elaine Angelino
• Nicholas Larus-Stone
• Daniel Alabi
• Margo Seltzer
• Cynthia Rudin

Improved Degree Bounds and Full Spectrum Power Laws in Preferential Attachment Networks

• Chen Avin
• Zvi Lotker
• Yinon Nahum
• David Peleg

Unsupervised Network Discovery for Brain Imaging Data

• Zilong Bai
• Peter Walker
• Anna Tschiffely
• Fei Wang
• Ian Davidson

Patient Subtyping via Time-Aware LSTM Networks

• Inci M. Baytas
• Cao Xiao
• Xi Zhang
• Fei Wang
• Anil K. Jain
• Jiayu Zhou

Robust Top-k Multiclass SVM for Visual Category Recognition

• Xiaojun Chang
• Yao-Liang Yu
• Yi Yang

KATE: K-Competitive Autoencoder for Text

• Yu Chen
• Mohammed J. Zaki

A Minimal Variance Estimator for the Cardinality of Big Data Set Intersection

• Reuven Cohen
• Liran Katzir
• Aviv Yehezkel

HyperLogLog Hyperextended: Sketches for Concave Sublinear Frequency Statistics

• Edith Cohen

Fast Enumeration of Large k-Plexes

• Alessio Conte
• Donatella Firmani
• Caterina Mordente
• Maurizio Patrignani
• Riccardo Torlone

Matrix Profile V: A Generic Technique to Incorporate Domain Knowledge into Motif Discovery

• Hoang Anh Dau
• Eamonn Keogh

metapath2vec: Scalable Representation Learning for Heterogeneous Networks

• Yuxiao Dong
• Nitesh V. Chawla
• Ananthram Swami

Ego-Splitting Framework: from Non-Overlapping to Overlapping Clusters

• Alessandro Epasto
• Silvio Lattanzi
• Renato Paes Leme

Contextual Motifs: Increasing the Utility of Motifs using Contextual Data

• Ian Fox
• Lynn Ang
• Mamta Jaiswal
• Rodica Pop-Busui
• Jenna Wiens

Unsupervised P2P Rental Recommendations via Integer Programming

• Yanjie Fu
• Guannan Liu
• Mingfei Teng
• Charu Aggarwal

The Co-Evolution Model for Social Network Evolving and Opinion Migration

• Yupeng Gu
• Yizhou Sun
• Jianxi Gao

Groups-Keeping Solution Path Algorithm for Sparse Regression with Automatic Feature Grouping

• Bin Gu
• Guodong Liu
• Heng Huang

Clustering Individual Transactional Data for Masses of Users

• Riccardo Guidotti
• Anna Monreale
• Mirco Nanni
• Fosca Giannotti
• Dino Pedreschi

Network Inference via the Time-Varying Graphical Lasso

• David Hallac
• Youngsuk Park
• Stephen Boyd
• Jure Leskovec

Toeplitz Inverse Covariance-Based Clustering of Multivariate Time Series Data

• David Hallac
• Sagar Vare
• Stephen Boyd
• Jure Leskovec

Efficient Correlated Topic Modeling with Topic Embedding

• Junxian He
• Zhiting Hu
• Taylor Berg-Kirkpatrick
• Ying Huang
• Eric P. Xing

Accelerating Innovation Through Analogy Mining

• Tom Hope
• Joel Chan
• Aniket Kittur
• Dafna Shahaf

Communication-Efficient Distributed Block Minimization for Nonlinear Kernel Machines

• Cho-Jui Hsieh
• Si Si
• Inderjit S. Dhillon

A Hierarchical Algorithm for Extreme Clustering

• Ari Kobren
• Nicholas Monath
• Akshay Krishnamurthy
• Andrew McCallum

Estimating Treatment Effect in the Wild via Differentiated Confounder Balancing

• Kun Kuang
• Peng Cui
• Bo Li
• Meng Jiang
• Shiqiang Yang

The Selective Labels Problem: Evaluating Algorithmic Predictions in the Presence of Unobservables

• Himabindu Lakkaraju
• Jon Kleinberg
• Jure Leskovec
• Jens Ludwig
• Sendhil Mullainathan

Constructivism Learning: A Learning Paradigm for Transparent Predictive Analytics

• Xiaoli Li
• Jun Huan

Is the Whole Greater Than the Sum of Its Parts?

• Liangyue Li
• Hanghang Tong
• Yong Wang
• Conglei Shi
• Nan Cao
• Norbou Buchler

Collaborative Variational Autoencoder for Recommender Systems

• Xiaopeng Li
• James She

Linearized GMM Kernels and Normalized Random Fourier Features

• Ping Li

Discrete Content-aware Matrix Factorization

• Defu Lian
• Rui Liu
• Yong Ge
• Kai Zheng
• Xing Xie
• Longbing Cao

Effective and Real-time In-App Activity Analysis in Encrypted Internet Traffic Streams

• Junming Liu
• Yanjie Fu
• Jingci Ming
• Yong Ren
• Leilei Sun
• Hui Xiong

Functional Annotation of Human Protein Coding Isoforms via Non-convex Multi-Instance Learning

• Tingjin Luo
• Weizhong Zhang
• Shang Qiu
• Yang Yang
• Dongyun Yi
• Guangtao Wang
• Jieping Ye
• Jie Wang

Discovering Reliable Approximate Functional Dependencies

• Panagiotis Mandros
• Mario Boley
• Jilles Vreeken

Towards an Optimal Subspace for K-Means

• Dominik Mautz
• Wei Ye
• Claudia Plant
• Christian Böhm

SPARTan: Scalable PARAFAC2 for Large & Sparse Data

• Ioakeim Perros
• Evangelos E. Papalexakis
• Fei Wang
• Richard Vuduc
• Elizabeth Searles
• Michael Thompson
• Jimeng Sun

struc2vec: Learning Node Representations from Structural Identity

• Leonardo F.R. Ribeiro
• Pedro H.P. Saverese
• Daniel R. Figueiredo

Similarity Forests

• Saket Sathe
• Charu C. Aggarwal

Online Ranking with Constraints: A Primal-Dual Algorithm and Applications to Web Traffic-Shaping

• Parikshit Shah
• Akshay Soni
• Troy Chevalier

On Finding Socially Tenuous Groups for Online Social Networks

• Chih-Ya Shen
• Liang-Hao Huang
• De-Nian Yang
• Hong-Han Shuai
• Wang-Chien Lee
• Ming-Syan Chen

PReP: Path-Based Relevance from a Probabilistic Perspective in Heterogeneous Information Networks

• Yu Shi
• Po-Wei Chan
• Honglei Zhuang
• Huan Gui
• Jiawei Han

Multi-Aspect Streaming Tensor Completion

• Qingquan Song
• Xiao Huang
• Hancheng Ge
• James Caverlee
• Xia Hu

Scalable and Sustainable Deep Learning via Randomized Hashing

• Ryan Spring
• Anshumali Shrivastava

AnnexML: Approximate Nearest Neighbor Search for Extreme Multi-label Classification

• Yukihiro Tagami

Interpretable Predictions of Tree-based Ensembles via Actionable Feature Tweaking

• Gabriele Tolomei
• Fabrizio Silvestri
• Andrew Haines
• Mounia Lalmas

Structural Deep Brain Network Mining

• Shen Wang
• Lifang He
• Bokai Cao
• Chun-Ta Lu
• Philip S. Yu
• Ann B. Ragin

Randomized Feature Engineering as a Fast and Accurate Alternative to Kernel Methods

• Suhang Wang
• Charu Aggarwal
• Huan Liu

Human Mobility Synchronization and Trip Purpose Detection with Mixture of Hawkes Processes

• Pengfei Wang
• Yanjie Fu
• Guannan Liu
• Wenqing Hu
• Charu Aggarwal

FORA: Simple and Effective Approximate Single-Source Personalized PageRank

• Sibo Wang
• Renchi Yang
• Xiaokui Xiao
• Zhewei Wei
• Yin Yang

Large-scale Collaborative Ranking in Near-Linear Time

• Liwei Wu
• Cho-Jui Hsieh
• James Sharpnack

HoORaYs: High-order Optimization of Rating Distance for Recommender Systems

• Jingwei Xu
• Yuan Yao
• Hanghang Tong
• Xianping Tao
• Jian Lu

Collaboratively Improving Topic Discovery and Word Embeddings by Coordinating Global and Local Contexts

• Guangxu Xun
• Yaliang Li
• Jing Gao
• Aidong Zhang

PPDsparse: A Parallel Primal-Dual Sparse Method for Extreme Classification

• Ian E.H. Yen
• Xiangru Huang
• Wei Dai
• Pradeep Ravikumar
• Inderjit Dhillon
• Eric Xing

Local Higher-Order Graph Clustering

• Hao Yin
• Austin R. Benson
• Jure Leskovec
• David F. Gleich

Long Short Memory Process: Modeling Growth Dynamics of Microscopic Social Connectivity

• Chengxi Zang
• Peng Cui
• Christos Faloutsos
• Wenwu Zhu

Weisfeiler-Lehman Neural Machine for Link Prediction

• Muhan Zhang
• Yixin Chen

EmbedJoin: Efficient Edit Similarity Joins via Embeddings

• Haoyu Zhang
• Qin Zhang

TrioVecEvent: Embedding-Based Online Local Event Detection in Geo-Tagged Tweet Streams

• Chao Zhang
• Liyuan Liu
• Dongming Lei
• Quan Yuan
• Honglei Zhuang
• Tim Hanratty
• Jiawei Han

Graph Edge Partitioning via Neighborhood Heuristic

• Chenzi Zhang
• Fan Wei
• Qin Liu
• Zhihao Gavin Tang
• Zhenguo Li

Randomization or Condensation?: Linear-Cost Matrix Sketching Via Cascaded Compression Sampling

• Kai Zhang
• Chuanren Liu
• Jie Zhang
• Hui Xiong
• Eric Xing
• Jieping Ye

Tracking the Dynamics in Crowdfunding

• Hongke Zhao
• Hefu Zhang
• Yong Ge
• Qi Liu
• Enhong Chen
• Huayu Li
• Le Wu

Meta-Graph Based Recommendation Fusion over Heterogeneous Information Networks

• Huan Zhao
• Quanming Yao
• Jianda Li
• Yangqiu Song
• Dik Lun Lee

Coresets for Kernel Regression

• Yan Zheng
• Jeff M. Phillips

A Local Algorithm for Structure-Preserving Graph Cut

• Dawei Zhou
• Si Zhang
• Mehmet Yigit Yildirim
• Scott Alcorn
• Hanghang Tong
• Hasan Davulcu
• Jingrui He

Anomaly Detection with Robust Deep Autoencoders

• Chong Zhou
• Randy C. Paffenroth

POSTER SESSION: KDD 2017 Research Papers (Poster Papers)

Effective Evaluation Using Logged Bandit Feedback from Multiple Loggers

• Aman Agarwal
• Soumya Basu
• Tobias Schnabel
• Thorsten Joachims

Tripoles: A New Class of Relationships in Time Series Data

• Saurabh Agrawal
• Gowtham Atluri
• Anuj Karpatne
• William Haltom
• Stefan Liess
• Snigdhansu Chatterjee
• Vipin Kumar

Post Processing Recommender Systems for Diversity

• Arda Antikacioglu
• R. Ravi

Aspect Based Recommendations: Recommending Items with the Most Valuable Aspects Based on User Reviews

• Konstantin Bauman
• Bing Liu
• Alexander Tuzhilin

Bolt: Accelerated Data Mining with Fast Vector Compression

• Davis W. Blalock
• John V. Guttag

Robust Spectral Clustering for Noisy Data: Modeling Sparse Corruptions Improves Latent Embeddings

• Aleksandar Bojchevski
• Yves Matkovic
• Stephan Günnemann

DeepMood: Modeling Mobile Phone Typing Dynamics for Mood Detection

• Bokai Cao
• Lei Zheng
• Chenwei Zhang
• Philip S. Yu
• Andrea Piscitello
• John Zulueta
• Olu Ajilore
• Kelly Ryan
• Alex D. Leow

Fast Newton Hard Thresholding Pursuit for Sparsity Constrained Nonconvex Optimization

• Jinghui Chen
• Quanquan Gu

On Sampling Strategies for Neural Network-based Collaborative Filtering

• Ting Chen
• Yizhou Sun
• Yue Shi
• Liangjie Hong

Unsupervised Feature Selection in Signed Social Networks

• Kewei Cheng
• Jundong Li
• Huan Liu

GRAM: Graph-based Attention Model for Healthcare Representation Learning

• Edward Choi
• Mohammad Taha Bahadori
• Le Song
• Walter F. Stewart
• Jimeng Sun

Algorithmic Decision Making and the Cost of Fairness

• Sam Corbett-Davies
• Emma Pierson
• Avi Feller
• Sharad Goel
• Aziz Huq

Structural Diversity and Homophily: A Study Across More Than One Hundred Big Networks

• Yuxiao Dong
• Reid A. Johnson
• Jian Xu
• Nitesh V. Chawla

Revisiting Power-law Distributions in Spectra of Real World Networks

• Nicole Eikmeier
• David F. Gleich

REMIX: Automated Exploration for Interactive Outlier Detection

• Yanjie Fu
• Charu Aggarwal
• Srinivasan Parthasarathy
• Deepak S. Turaga
• Hui Xiong

Anarchists, Unite: Practical Entropy Approximation for Distributed Streams

• Moshe Gabel
• Daniel Keren
• Assaf Schuster

Recurrent Poisson Factorization for Temporal Recommendation

• Seyed Abbas Hosseini
• Keivan Alizadeh
• Ali Khodadadi
• Ali Arabzadeh
• Mehrdad Farajtabar
• Hongyuan Zha
• Hamid R. Rabiee

SPOT: Sparse Optimal Transformations for High Dimensional Variable Selection and Exploratory Regression Analysis

• Qiming Huang
• Michael Zhu

Incremental Dual-memory LSTM in Land Cover Prediction

• Xiaowei Jia
• Ankush Khandelwal
• Guruprasad Nayak
• James Gerber
• Kimberly Carlson
• Paul West
• Vipin Kumar

MetaPAD: Meta Pattern Discovery from Massive Text Corpora

• Meng Jiang
• Jingbo Shang
• Taylor Cassidy
• Xiang Ren
• Lance M. Kaplan
• Timothy P. Hanratty
• Jiawei Han

Federated Tensor Factorization for Computational Phenotyping

• Yejin Kim
• Jimeng Sun
• Hwanjo Yu
• Xiaoqian Jiang

Statistical Emerging Pattern Mining with Multiple Testing Correction

• Junpei Komiyama
• Masakazu Ishihata
• Hiroki Arimura
• Takashi Nishibayashi
• Shin-ichi Minato

Semi-Supervised Techniques for Mining Learning Outcomes and Prerequisites

• Igor Labutov
• Yun Huang
• Peter Brusilovsky
• Daqing He

Prospecting the Career Development of Talents: A Survival Analysis Perspective

• Huayu Li
• Yong Ge
• Hengshu Zhu
• Hui Xiong
• Hongke Zhao

A Context-aware Attention Network for Interactive Question Answering

• Huayu Li
• Martin Renqiang Min
• Yong Ge
• Asim Kadav

Distributed Multi-Task Relationship Learning

• Sulin Liu
• Sinno Jialin Pan
• Qirong Ho

Point-of-Interest Demand Modeling with Human Mobility Patterns

• Yanchi Liu
• Chuanren Liu
• Xinjiang Lu
• Mingfei Teng
• Hengshu Zhu
• Hui Xiong

Functional Zone Based Hierarchical Demand Prediction For Bike System Expansion

• Junming Liu
• Leilei Sun
• Qiao Li
• Jingci Ming
• Yanchi Liu
• Hui Xiong

Unsupervised Discovery of Drug Side-Effects from Heterogeneous Data Sources

• Fenglong Ma
• Chuishi Meng
• Houping Xiao
• Qi Li
• Jing Gao
• Lu Su
• Aidong Zhang

Let’s See Your Digits: Anomalous-State Detection using Benford’s Law

• Samuel Maurus
• Claudia Plant

Mixture Factorized Ornstein-Uhlenbeck Processes for Time-Series Forecasting

• Guo-Jun Qi
• Jiliang Tang
• Jingdong Wang
• Jiebo Luo

Automatic Synonym Discovery with Knowledge Bases

• Meng Qu
• Xiang Ren
• Jiawei Han

An Alternative to NCD for Large Sequences, Lempel-Ziv Jaccard Distance

• Edward Raff
• Charles Nicholas

Inferring the Strength of Social Ties: A Community-Driven Approach

• Polina Rozenshtein
• Nikolaj Tatti
• Aristides Gionis

Detecting Network Effects: Randomizing Over Randomized Experiments

• Martin Saveski
• Jean Pouget-Abadie
• Guillaume Saint-Jacques
• Weitao Duan
• Souvik Ghosh
• Ya Xu
• Edoardo M. Airoldi

When is a Network a Network?: Multi-Order Graphical Model Selection in Pathways and Temporal Networks

• Ingo Scholtes

ReasoNet: Learning to Stop Reading in Machine Comprehension

• Yelong Shen
• Po-Sen Huang
• Jianfeng Gao
• Weizhu Chen

DenseAlert: Incremental Dense-Subtensor Detection in Tensor Streams

• Kijung Shin
• Bryan Hooi
• Jisu Kim
• Christos Faloutsos

Anomaly Detection in Streams with Extreme Value Theory

• Alban Siffer
• Pierre-Alain Fouque
• Alexandre Termier
• Christine Largouet

Relay-Linking Models for Prominence and Obsolescence in Evolving Networks

• Mayank Singh
• Rajdeep Sarkar
• Pawan Goyal
• Animesh Mukherjee
• Soumen Chakrabarti

PAMAE: Parallel k-Medoids Clustering with High Accuracy and Efficiency

• Hwanjun Song
• Jae-Gil Lee
• Wook-Shin Han

Sparse Compositional Local Metric Learning

• Joseph St.Amand
• Jun Huan

End-to-end Learning for Short Text Expansion

• Jian Tang
• Yue Wang
• Kai Zheng
• Qiaozhu Mei

Construction of Directed 2K Graphs

• Bálint Tillman
• Athina Markopoulou
• Carter T. Butts
• Minas Gjoka

Optimized Risk Scores

• Berk Ustun
• Cynthia Rudin

A Location-Sentiment-Aware Recommender System for Both Home-Town and Out-of-Town Users

• Hao Wang
• Yanmei Fu
• Qinyong Wang
• Hongzhi Yin
• Changying Du
• Hui Xiong

Adversary Resistant Deep Neural Networks with an Application to Malware Detection

• Qinglong Wang
• Wenbo Guo
• Kaixuan Zhang
• Alexander G. Ororbia, II
• Xinyu Xing
• Xue Liu
• C. Lee Giles

Multi-Modality Disease Modeling via Collective Deep Matrix Factorization

• Qi Wang
• Mengying Sun
• Liang Zhan
• Paul Thompson
• Shuiwang Ji
• Jiayu Zhou

Decomposed Normalized Maximum Likelihood Codelength Criterion for Selecting Hierarchical Latent Variable Models

• Tianyi Wu
• Shinya Sugawara
• Kenji Yamanishi

Structural Event Detection from Log Messages

• Fei Wu
• Pranay Anchuri
• Zhenhui Li

Retrospective Higher-Order Markov Processes for User Trails

• Tao Wu
• David F. Gleich

Privacy-Preserving Distributed Multi-Task Learning with Asynchronous Updates

• Liyang Xie
• Inci M. Baytas
• Kaixiang Lin
• Jiayu Zhou

Evaluating U.S. Electoral Representation with a Joint Statistical Model of Congressional Roll-Calls, Legislative Text, and Voter Registration Data

• Zhengming Xing
• Sunshine Hillygus
• Lawrence Carin

Convex Factorization Machine for Toxicogenomics Prediction

• Makoto Yamada
• Wenzhao Lian
• Amit Goyal
• Jianhui Chen
• Kishan Wimalawarne
• Suleiman A. Khan
• Samuel Kaski
• Hiroshi Mamitsuka
• Yi Chang

Distributed Local Outlier Detection in Big Data

• Yizhou Yan
• Lei Cao
• Caitlin Kulhman
• Elke Rundensteiner

Scalable Top-n Local Outlier Detection

• Yizhou Yan
• Lei Cao
• Elke A. Rundensteiner

Bridging Collaborative Filtering and Semi-Supervised Learning: A Neural Approach for POI Recommendation

• Carl Yang
• Lanxiao Bai
• Chao Zhang
• Quan Yuan
• Jiawei Han

Multi-task Function-on-function Regression with Co-grouping Structured Sparsity

• Pei Yang
• Qi Tan
• Jingrui He

Learning from Labeled and Unlabeled Vertices in Networks

• Wei Ye
• Linfei Zhou
• Dominik Mautz
• Claudia Plant
• Christian Böhm

Small Batch or Large Batch?: Gaussian Walk with Rebound Can Teach

• Peifeng Yin
• Ping Luo
• Taiga Nakamura

Learning from Multiple Teacher Networks

• Shan You
• Chang Xu
• Chao Xu
• Dacheng Tao

A Temporally Heterogeneous Survival Framework with Application to Social Behavior Dynamics

• Linyun Yu
• Peng Cui
• Chaoming Song
• Tianyang Zhang
• Shiqiang Yang

Inductive Semi-supervised Multi-Label Learning with Co-Training

• Wang Zhan
• Min-Ling Zhang

LEAP: Learning to Prescribe Effective and Safe Treatment Combinations for Multimorbidity

• Yutao Zhang
• Robert Chen
• Jie Tang
• Walter F. Stewart
• Jimeng Sun

Visualizing Attributed Graphs via Terrain Metaphor

• Yang Zhang
• Yusu Wang
• Srinivasan Parthasarathy

Achieving Non-Discrimination in Data Release

• Lu Zhang
• Yongkai Wu
• Xintao Wu

SESSION: KDD 2017 Applied Data Science Papers (Oral Papers)

Using Convolutional Networks and Satellite Imagery to Identify Patterns in Urban Environments at a Large Scale

• Adrian Albert
• Jasleen Kaur
• Marta C. Gonzalez

Luck is Hard to Beat: The Difficulty of Sports Prediction

• Raquel Y.S. Aoki
• Renato M. Assuncao
• Pedro O.S. Vaz de Melo

Planning Bike Lanes based on Sharing-Bikes’ Trajectories

• Jie Bao
• Tianfu He
• Sijie Ruan
• Yanhua Li
• Yu Zheng

TFX: A TensorFlow-Based Production-Scale Machine Learning Platform

• Denis Baylor
• Eric Breck
• Heng-Tze Cheng
• Noah Fiedel
• Chuan Yu Foo
• Zakaria Haque
• Salem Haykal
• Mustafa Ispir
• Vihan Jain
• Levent Koc
• Chiu Yuen Koo
• Lukasz Lew
• Clemens Mewald
• Akshay Naresh Modi
• Neoklis Polyzotis
• Sukriti Ramesh
• Sudip Roy
• Steven Euijong Whang
• Martin Wicke
• Jarek Wilkiewicz
• Xin Zhang
• Martin Zinkevich

LiJAR: A System for Job Application Redistribution towards Efficient Career Marketplace

• Fedor Borisyuk
• Liang Zhang
• Krishnaram Kenthapadi

A Data Science Approach to Understanding Residential Water Contamination in Flint

• Alex Chojnacki
• Chengyu Dai
• Arya Farahi
• Guangsha Shi
• Jared Webb
• Daniel T. Zhang
• Jacob Abernethy
• Eric Schwartz

Estimation of Recent Ancestral Origins of Individuals on a Large Scale

• Ross E. Curtis
• Ahna R. Girshick

A Dirty Dozen: Twelve Common Metric Interpretation Pitfalls in Online Controlled Experiments

• Pavel Dmitriev
• Somit Gupta
• Dong Woo Kim
• Garnet Vaz

A Century of Science: Globalization of Scientific Collaborations, Citations, and Innovations

• Yuxiao Dong
• Hao Ma
• Zhihong Shen
• Kuansan Wang

FIRST: Fast Interactive Attributed Subgraph Matching

• Boxin Du
• Si Zhang
• Nan Cao
• Hanghang Tong

Prognosis and Diagnosis of Parkinson’s Disease Using Multi-Task Learning

• Saba Emrani
• Anya McGuirk
• Wei Xiao

A Data Mining Framework for Valuing Large Portfolios of Variable Annuities

• Guojun Gan
• Jimmy Xiangji Huang

GELL: Automatic Extraction of Epidemiological Line Lists from Open Sources

• Saurav Ghosh
• Prithwish Chakraborty
• Bryan L. Lewis
• Maimuna S. Majumder
• Emily Cohn
• John S. Brownstein
• Madhav V. Marathe
• Naren Ramakrishnan

Google Vizier: A Service for Black-Box Optimization

• Daniel Golovin
• Benjamin Solnik
• Subhodeep Moitra
• Greg Kochanski
• John Karro