Home
Conferences
KDD 2024 - Barcelona, Spain
KDD 2023 - Long Beach, CA
KDD 2022 - Washington D.C.
KDD 2021 - Singapore
KDD Proceedings Archives
KDD Cup Archives
Awards
Innovation Award
Service Award
Test of Time Award
Dissertation Award
Best Paper Award
Rising Star Award
Publications
SIGKDD Explorations
SIGKDD Curriculum
News
About
About SIGKDD
SIGKDD In The News
Join SIGKDD
KDD Local Chapters
Contact
SIGKDD Proceedings
Home
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
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
Copyrights © 2024 All Rights Reserved - SIGKDD
ACM Code of Conduct