SIGKDD Proceedings

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


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
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