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23rd KDD 2017: Halifax, NS, Canada
- Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13 - 17, 2017. ACM 2017, ISBN 978-1-4503-4887-4
KDD 2017 Keynote Talks
- Cynthia Dwork:
What's Fair? 1 - Renée J. Miller:
The Future of Data Integration. 3 - Bin Yu:
Three Principles of Data Science: Predictability, Stability and Computability. 5
KDD 2017 Applied Invited Talks
- Usama M. Fayyad, Evangelos Simoudis, Ashok Srivastava:
Foreword to the Applied Data Science: Invited Talks Track at KDD-2017. 7-8 - Eduardo Ariño de la Rubia:
More than the Sum of its Parts: Building Domino Data Lab. 9 - Andy Berglund:
Mining Big Data in NeuroGenetics to Understand Muscular Dystrophy. 11 - Josh Bloom:
Industrial Machine Learning. 13 - Longbing Cao
:
Behavior Informatics to Discover Behavior Insight for Active and Tailored Client Management. 15-16 - Paritosh Desai:
It Takes More than Math and Engineering to Hit the Bullseye with Data. 17 - Jonathan P. How:
Planning and Learning under Uncertainty: Theory and Practice. 19 - Anuj Karpatne, Vipin Kumar:
Big Data in Climate: Opportunities and Challenges for Machine Learning. 21-22 - Mainak Mazumdar:
Addressing Challenges with Big Data for Media Measurement. 23 - Szilárd Pafka:
Machine Learning Software in Practice: Quo Vadis? 25 - Rajesh Parekh:
Designing AI at Scale to Power Everyday Life. 27 - David Potere:
Spaceborne Data Enters the Mainstream. 29
KDD 2017 Panels
- Usama M. Fayyad, Arno Candel, Eduardo Ariño de la Rubia, Szilárd Pafka, Anthony Chong, Jeong-Yoon Lee:
Benchmarks and Process Management in Data Science: Will We Ever Get Over the Mess? 31-32 - Muthu Muthukrishnan, Andrew Tomkins, Larry P. Heck, Alborz Geramifard, Deepak Agarwal:
The Future of Artificially Intelligent Assistants. 33-34
KDD 2017 Research Papers (Oral Papers)
- Elaine Angelino, Nicholas Larus-Stone, Daniel Alabi, Margo I. Seltzer, Cynthia Rudin:
Learning Certifiably Optimal Rule Lists. 35-44 - Chen Avin
Improved Degree Bounds and Full Spectrum Power Laws in Preferential Attachment Networks. 45-53 - Zilong Bai
Unsupervised Network Discovery for Brain Imaging Data. 55-64 - Inci M. Baytas
Patient Subtyping via Time-Aware LSTM Networks. 65-74 - Xiaojun Chang
Robust Top-k Multiclass SVM for Visual Category Recognition. 75-83 - Yu Chen, Mohammed J. Zaki
KATE: K-Competitive Autoencoder for Text. 85-94 - Reuven Cohen, Liran Katzir, Aviv Yehezkel:
A Minimal Variance Estimator for the Cardinality of Big Data Set Intersection. 95-103 - Edith Cohen:
HyperLogLog Hyperextended: Sketches for Concave Sublinear Frequency Statistics. 105-114 - Alessio Conte, Donatella Firmani
Fast Enumeration of Large k-Plexes. 115-124 - Hoang Anh Dau, Eamonn J. Keogh:
Matrix Profile V: A Generic Technique to Incorporate Domain Knowledge into Motif Discovery. 125-134 - Yuxiao Dong, Nitesh V. Chawla
metapath2vec: Scalable Representation Learning for Heterogeneous Networks. 135-144 - Alessandro Epasto
Ego-Splitting Framework: from Non-Overlapping to Overlapping Clusters. 145-154 - Ian Fox, Lynn Ang, Mamta Jaiswal, Rodica Pop-Busui
Contextual Motifs: Increasing the Utility of Motifs using Contextual Data. 155-164 - Yanjie Fu, Guannan Liu, Mingfei Teng, Charu C. Aggarwal:
Unsupervised P2P Rental Recommendations via Integer Programming. 165-173 - Yupeng Gu, Yizhou Sun, Jianxi Gao
The Co-Evolution Model for Social Network Evolving and Opinion Migration. 175-184 - Bin Gu, Guodong Liu, Heng Huang:
Groups-Keeping Solution Path Algorithm for Sparse Regression with Automatic Feature Grouping. 185-193 - Riccardo Guidotti, Anna Monreale, Mirco Nanni, Fosca Giannotti, Dino Pedreschi
Clustering Individual Transactional Data for Masses of Users. 195-204 - David Hallac, Youngsuk Park, Stephen P. Boyd, Jure Leskovec:
Network Inference via the Time-Varying Graphical Lasso. 205-213 - David Hallac, Sagar Vare, Stephen P. Boyd, Jure Leskovec:
Toeplitz Inverse Covariance-Based Clustering of Multivariate Time Series Data. 215-223 - Junxian He
Efficient Correlated Topic Modeling with Topic Embedding. 225-233 - Tom Hope
Accelerating Innovation Through Analogy Mining. 235-243 - Cho-Jui Hsieh, Si Si, Inderjit S. Dhillon:
Communication-Efficient Distributed Block Minimization for Nonlinear Kernel Machines. 245-254 - Ari Kobren, Nicholas Monath, Akshay Krishnamurthy, Andrew McCallum:
A Hierarchical Algorithm for Extreme Clustering. 255-264 - Kun Kuang, Peng Cui, Bo Li, Meng Jiang
Estimating Treatment Effect in the Wild via Differentiated Confounder Balancing. 265-274 - Himabindu Lakkaraju, Jon M. Kleinberg, Jure Leskovec, Jens Ludwig, Sendhil Mullainathan
The Selective Labels Problem: Evaluating Algorithmic Predictions in the Presence of Unobservables. 275-284 - Xiaoli Li, Jun Huan:
Constructivism Learning: A Learning Paradigm for Transparent Predictive Analytics. 285-294 - Liangyue Li, Hanghang Tong
Is the Whole Greater Than the Sum of Its Parts? 295-304 - Xiaopeng Li
Collaborative Variational Autoencoder for Recommender Systems. 305-314 - Ping Li:
Linearized GMM Kernels and Normalized Random Fourier Features. 315-324 - Defu Lian
Discrete Content-aware Matrix Factorization. 325-334 - Junming Liu
Effective and Real-time In-App Activity Analysis in Encrypted Internet Traffic Streams. 335-344 - Tingjin Luo
Functional Annotation of Human Protein Coding Isoforms via Non-convex Multi-Instance Learning. 345-354 - Panagiotis Mandros, Mario Boley
Discovering Reliable Approximate Functional Dependencies. 355-363 - Dominik Mautz
Towards an Optimal Subspace for K-Means. 365-373 - Ioakeim Perros, Evangelos E. Papalexakis
SPARTan: Scalable PARAFAC2 for Large & Sparse Data. 375-384 - Leonardo Filipe Rodrigues Ribeiro
struc2vec: Learning Node Representations from Structural Identity. 385-394 - Saket Sathe, Charu C. Aggarwal:
Similarity Forests. 395-403 - Parikshit Shah, Akshay Soni, Troy Chevalier:
Online Ranking with Constraints: A Primal-Dual Algorithm and Applications to Web Traffic-Shaping. 405-414 - Chih-Ya Shen, Liang-Hao Huang, De-Nian Yang
On Finding Socially Tenuous Groups for Online Social Networks. 415-424 - Yu Shi, Po-Wei Chan, Honglei Zhuang, Huan Gui, Jiawei Han:
PReP: Path-Based Relevance from a Probabilistic Perspective in Heterogeneous Information Networks. 425-434 - Qingquan Song, Xiao Huang
Multi-Aspect Streaming Tensor Completion. 435-443 - Ryan Spring, Anshumali Shrivastava:
Scalable and Sustainable Deep Learning via Randomized Hashing. 445-454 - Yukihiro Tagami:
AnnexML: Approximate Nearest Neighbor Search for Extreme Multi-label Classification. 455-464 - Gabriele Tolomei, Fabrizio Silvestri
Interpretable Predictions of Tree-based Ensembles via Actionable Feature Tweaking. 465-474 - Shen Wang, Lifang He
Structural Deep Brain Network Mining. 475-484 - Suhang Wang
Randomized Feature Engineering as a Fast and Accurate Alternative to Kernel Methods. 485-494 - Pengfei Wang
Human Mobility Synchronization and Trip Purpose Detection with Mixture of Hawkes Processes. 495-503 - Sibo Wang
FORA: Simple and Effective Approximate Single-Source Personalized PageRank. 505-514 - Liwei Wu, Cho-Jui Hsieh, James Sharpnack:
Large-scale Collaborative Ranking in Near-Linear Time. 515-524 - Jingwei Xu, Yuan Yao, Hanghang Tong
HoORaYs: High-order Optimization of Rating Distance for Recommender Systems. 525-534 - Guangxu Xun
Collaboratively Improving Topic Discovery and Word Embeddings by Coordinating Global and Local Contexts. 535-543 - Ian En-Hsu Yen, Xiangru Huang, Wei Dai, Pradeep Ravikumar, Inderjit S. Dhillon, Eric P. Xing:
PPDsparse: A Parallel Primal-Dual Sparse Method for Extreme Classification. 545-553 - Hao Yin, Austin R. Benson, Jure Leskovec, David F. Gleich
Local Higher-Order Graph Clustering. 555-564 - Chengxi Zang
Long Short Memory Process: Modeling Growth Dynamics of Microscopic Social Connectivity. 565-574 - Muhan Zhang, Yixin Chen:
Weisfeiler-Lehman Neural Machine for Link Prediction. 575-583 - Haoyu Zhang, Qin Zhang
EmbedJoin: Efficient Edit Similarity Joins via Embeddings. 585-594 - Chao Zhang
TrioVecEvent: Embedding-Based Online Local Event Detection in Geo-Tagged Tweet Streams. 595-604 - Chenzi Zhang, Fan Wei, Qin Liu
Graph Edge Partitioning via Neighborhood Heuristic. 605-614 - Kai Zhang, Chuanren Liu
Randomization or Condensation?: Linear-Cost Matrix Sketching Via Cascaded Compression Sampling. 615-623 - Hongke Zhao, Hefu Zhang, Yong Ge, Qi Liu, Enhong Chen, Huayu Li, Le Wu:
Tracking the Dynamics in Crowdfunding. 625-634 - Huan Zhao, Quanming Yao, Jianda Li, Yangqiu Song, Dik Lun Lee:
Meta-Graph Based Recommendation Fusion over Heterogeneous Information Networks. 635-644 - Yan Zheng, Jeff M. Phillips:
Coresets for Kernel Regression. 645-654 - Dawei Zhou, Si Zhang, Mehmet Yigit Yildirim, Scott Alcorn, Hanghang Tong
A Local Algorithm for Structure-Preserving Graph Cut. 655-664 - Chong Zhou, Randy C. Paffenroth
Anomaly Detection with Robust Deep Autoencoders. 665-674
KDD 2017 Research Papers (Poster Papers)
- Aman Agarwal, Soumya Basu, Tobias Schnabel, Thorsten Joachims:
Effective Evaluation Using Logged Bandit Feedback from Multiple Loggers. 687-696 - Saurabh Agrawal, Gowtham Atluri, Anuj Karpatne, William Haltom, Stefan Liess
Tripoles: A New Class of Relationships in Time Series Data. 697-706 - Arda Antikacioglu, R. Ravi:
Post Processing Recommender Systems for Diversity. 707-716 - Konstantin Bauman
Aspect Based Recommendations: Recommending Items with the Most Valuable Aspects Based on User Reviews. 717-725 - Davis W. Blalock, John V. Guttag:
Bolt: Accelerated Data Mining with Fast Vector Compression. 727-735 - Aleksandar Bojchevski, Yves Matkovic, Stephan Günnemann:
Robust Spectral Clustering for Noisy Data: Modeling Sparse Corruptions Improves Latent Embeddings. 737-746 - Bokai Cao, Lei Zheng, Chenwei Zhang, Philip S. Yu, Andrea Piscitello, John Zulueta
DeepMood: Modeling Mobile Phone Typing Dynamics for Mood Detection. 747-755 - Jinghui Chen, Quanquan Gu:
Fast Newton Hard Thresholding Pursuit for Sparsity Constrained Nonconvex Optimization. 757-766 - Ting Chen, Yizhou Sun, Yue Shi, Liangjie Hong:
On Sampling Strategies for Neural Network-based Collaborative Filtering. 767-776 - Kewei Cheng, Jundong Li, Huan Liu:
Unsupervised Feature Selection in Signed Social Networks. 777-786 - Edward Choi
GRAM: Graph-based Attention Model for Healthcare Representation Learning. 787-795 - Sam Corbett-Davies, Emma Pierson, Avi Feller
Algorithmic Decision Making and the Cost of Fairness. 797-806 - Yuxiao Dong, Reid A. Johnson
Structural Diversity and Homophily: A Study Across More Than One Hundred Big Networks. 807-816 - Nicole Eikmeier, David F. Gleich
Revisiting Power-law Distributions in Spectra of Real World Networks. 817-826 - Yanjie Fu, Charu C. Aggarwal, Srinivasan Parthasarathy, Deepak S. Turaga, Hui Xiong:
REMIX: Automated Exploration for Interactive Outlier Detection. 827-835 - Moshe Gabel, Daniel Keren, Assaf Schuster:
Anarchists, Unite: Practical Entropy Approximation for Distributed Streams. 837-846 - Seyyed Abbas Hosseini
Recurrent Poisson Factorization for Temporal Recommendation. 847-855 - Qiming Huang, Michael Zhu:
SPOT: Sparse Optimal Transformations for High Dimensional Variable Selection and Exploratory Regression Analysis. 857-865 - Xiaowei Jia, Ankush Khandelwal, Guruprasad Nayak
Incremental Dual-memory LSTM in Land Cover Prediction. 867-876 - Meng Jiang
MetaPAD: Meta Pattern Discovery from Massive Text Corpora. 877-886 - Yejin Kim, Jimeng Sun
Federated Tensor Factorization for Computational Phenotyping. 887-895 - Junpei Komiyama, Masakazu Ishihata, Hiroki Arimura, Takashi Nishibayashi, Shin-ichi Minato:
Statistical Emerging Pattern Mining with Multiple Testing Correction. 897-906 - Igor Labutov, Yun Huang, Peter Brusilovsky
Semi-Supervised Techniques for Mining Learning Outcomes and Prerequisites. 907-915 - Huayu Li
Prospecting the Career Development of Talents: A Survival Analysis Perspective. 917-925 - Huayu Li
A Context-aware Attention Network for Interactive Question Answering. 927-935 - Sulin Liu, Sinno Jialin Pan
Distributed Multi-Task Relationship Learning. 937-946 - Yanchi Liu, Chuanren Liu
Point-of-Interest Demand Modeling with Human Mobility Patterns. 947-955 - Junming Liu
Functional Zone Based Hierarchical Demand Prediction For Bike System Expansion. 957-966 - Fenglong Ma, Chuishi Meng, Houping Xiao, Qi Li, Jing Gao, Lu Su, Aidong Zhang:
Unsupervised Discovery of Drug Side-Effects from Heterogeneous Data Sources. 967-976 - Samuel Maurus, Claudia Plant
Let's See Your Digits: Anomalous-State Detection using Benford's Law. 977-986 - Guo-Jun Qi
Mixture Factorized Ornstein-Uhlenbeck Processes for Time-Series Forecasting. 987-995 - Meng Qu, Xiang Ren, Jiawei Han:
Automatic Synonym Discovery with Knowledge Bases. 997-1005 - Edward Raff
An Alternative to NCD for Large Sequences, Lempel-Ziv Jaccard Distance. 1007-1015 - Polina Rozenshtein, Nikolaj Tatti
Inferring the Strength of Social Ties: A Community-Driven Approach. 1017-1025 - Martin Saveski, Jean Pouget-Abadie, Guillaume Saint-Jacques, Weitao Duan, Souvik Ghosh, Ya Xu, Edoardo M. Airoldi:
Detecting Network Effects: Randomizing Over Randomized Experiments. 1027-1035 - Ingo Scholtes
When is a Network a Network?: Multi-Order Graphical Model Selection in Pathways and Temporal Networks. 1037-1046 - Yelong Shen, Po-Sen Huang, Jianfeng Gao, Weizhu Chen:
ReasoNet: Learning to Stop Reading in Machine Comprehension. 1047-1055 - Kijung Shin, Bryan Hooi, Jisu Kim, Christos Faloutsos:
DenseAlert: Incremental Dense-Subtensor Detection in Tensor Streams. 1057-1066 - Alban Siffer, Pierre-Alain Fouque
Anomaly Detection in Streams with Extreme Value Theory. 1067-1075 - Mayank Singh, Rajdeep Sarkar, Pawan Goyal, Animesh Mukherjee, Soumen Chakrabarti:
Relay-Linking Models for Prominence and Obsolescence in Evolving Networks. 1077-1086 - Hwanjun Song, Jae-Gil Lee, Wook-Shin Han:
PAMAE: Parallel k-Medoids Clustering with High Accuracy and Efficiency. 1087-1096 - Joseph St. Amand, Jun Huan:
Sparse Compositional Local Metric Learning. 1097-1104 - Jian Tang, Yue Wang, Kai Zheng, Qiaozhu Mei:
End-to-end Learning for Short Text Expansion. 1105-1113 - Bálint Tillman, Athina Markopoulou
Construction of Directed 2K Graphs. 1115-1124 - Berk Ustun
Optimized Risk Scores. 1125-1134 - Hao Wang, Yanmei Fu, Qinyong Wang, Hongzhi Yin
A Location-Sentiment-Aware Recommender System for Both Home-Town and Out-of-Town Users. 1135-1143 - Qinglong Wang, Wenbo Guo
Adversary Resistant Deep Neural Networks with an Application to Malware Detection. 1145-1153 - Qi Wang, Mengying Sun, Liang Zhan, Paul Thompson
Multi-Modality Disease Modeling via Collective Deep Matrix Factorization. 1155-1164 - Tianyi Wu, Shinya Sugawara
Decomposed Normalized Maximum Likelihood Codelength Criterion for Selecting Hierarchical Latent Variable Models. 1165-1174 - Fei Wu, Pranay Anchuri, Zhenhui Li:
Structural Event Detection from Log Messages. 1175-1184 - Tao Wu, David F. Gleich
Retrospective Higher-Order Markov Processes for User Trails. 1185-1194 - Liyang Xie, Inci M. Baytas
Privacy-Preserving Distributed Multi-Task Learning with Asynchronous Updates. 1195-1204 - Zhengming Xing, Sunshine Hillygus, Lawrence Carin
Evaluating U.S. Electoral Representation with a Joint Statistical Model of Congressional Roll-Calls, Legislative Text, and Voter Registration Data. 1205-1214 - Makoto Yamada
Convex Factorization Machine for Toxicogenomics Prediction. 1215-1224 - Yizhou Yan, Lei Cao
Distributed Local Outlier Detection in Big Data. 1225-1234 - Yizhou Yan, Lei Cao
Scalable Top-n Local Outlier Detection. 1235-1244 - Carl Yang, Lanxiao Bai, Chao Zhang
Bridging Collaborative Filtering and Semi-Supervised Learning: A Neural Approach for POI Recommendation. 1245-1254 - Pei Yang, Qi Tan, Jingrui He:
Multi-task Function-on-function Regression with Co-grouping Structured Sparsity. 1255-1264 - Wei Ye
Learning from Labeled and Unlabeled Vertices in Networks. 1265-1274 - Peifeng Yin, Ping Luo, Taiga Nakamura:
Small Batch or Large Batch?: Gaussian Walk with Rebound Can Teach. 1275-1284 - Shan You, Chang Xu
Learning from Multiple Teacher Networks. 1285-1294 - Linyun Yu, Peng Cui, Chaoming Song
A Temporally Heterogeneous Survival Framework with Application to Social Behavior Dynamics. 1295-1304 - Wang Zhan, Min-Ling Zhang
Inductive Semi-supervised Multi-Label Learning with Co-Training. 1305-1314 - Yutao Zhang, Robert Chen, Jie Tang, Walter F. Stewart, Jimeng Sun
LEAP: Learning to Prescribe Effective and Safe Treatment Combinations for Multimorbidity. 1315-1324 - Yang Zhang, Yusu Wang, Srinivasan Parthasarathy
Visualizing Attributed Graphs via Terrain Metaphor. 1325-1334 - Lu Zhang, Yongkai Wu
Achieving Non-Discrimination in Data Release. 1335-1344
KDD 2017 Applied Data Science Papers (Oral Papers)
- Adrian Albert, Jasleen Kaur, Marta C. González:
Using Convolutional Networks and Satellite Imagery to Identify Patterns in Urban Environments at a Large Scale. 1357-1366 - Raquel Y. S. Aoki, Renato Martins Assunção, Pedro O. S. Vaz de Melo
Luck is Hard to Beat: The Difficulty of Sports Prediction. 1367-1376 - Jie Bao, Tianfu He, Sijie Ruan, Yanhua Li, Yu Zheng:
Planning Bike Lanes based on Sharing-Bikes' Trajectories. 1377-1386 - 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:
TFX: A TensorFlow-Based Production-Scale Machine Learning Platform. 1387-1395 - Fedor Borisyuk, Liang Zhang, Krishnaram Kenthapadi:
LiJAR: A System for Job Application Redistribution towards Efficient Career Marketplace. 1397-1406 - Alex Chojnacki, Chengyu Dai, Arya Farahi
A Data Science Approach to Understanding Residential Water Contamination in Flint. 1407-1416 - Ross E. Curtis, Ahna Reza Girshick:
Estimation of Recent Ancestral Origins of Individuals on a Large Scale. 1417-1425 - Pavel A. Dmitriev, Somit Gupta, Dong Woo Kim, Garnet Jason Vaz:
A Dirty Dozen: Twelve Common Metric Interpretation Pitfalls in Online Controlled Experiments. 1427-1436 - Yuxiao Dong, Hao Ma, Zhihong Shen, Kuansan Wang:
A Century of Science: Globalization of Scientific Collaborations, Citations, and Innovations. 1437-1446 - Boxin Du, Si Zhang, Nan Cao, Hanghang Tong
FIRST: Fast Interactive Attributed Subgraph Matching. 1447-1456 - Saba Emrani, Anya McGuirk, Wei Xiao
Prognosis and Diagnosis of Parkinson's Disease Using Multi-Task Learning. 1457-1466 - Guojun Gan, Jimmy Xiangji Huang
A Data Mining Framework for Valuing Large Portfolios of Variable Annuities. 1467-1475 - Saurav Ghosh, Prithwish Chakraborty, Bryan L. Lewis, Maimuna S. Majumder, Emily Cohn, John S. Brownstein, Madhav V. Marathe, Naren Ramakrishnan
GELL: Automatic Extraction of Epidemiological Line Lists from Open Sources. 1477-1485 - Daniel Golovin, Benjamin Solnik, Subhodeep Moitra, Greg Kochanski, John Karro, D. Sculley:
Google Vizier: A Service for Black-Box Optimization. 1487-1495 - Jen J. Gong, Tristan Naumann, Peter Szolovits, John V. Guttag:
Predicting Clinical Outcomes Across Changing Electronic Health Record Systems. 1497-1505 - Shifu Hou, Yanfang Ye, Yangqiu Song, Melih Abdulhayoglu:
HinDroid: An Intelligent Android Malware Detection System Based on Structured Heterogeneous Information Network. 1507-1515 - Ramesh Johari, Pete Koomen, Leonid Pekelis, David Walsh:
Peeking at A/B Tests: Why it matters, and what to do about it. 1517-1525 - Danai Koutra, Abhilash Dighe, Smriti Bhagat, Udi Weinsberg, Stratis Ioannidis
PNP: Fast Path Ensemble Method for Movie Design. 1527-1536 - Zhaobin Kuang, Peggy L. Peissig, Vítor Santos Costa
Pharmacovigilance via Baseline Regularization with Large-Scale Longitudinal Observational Data. 1537-1546 - Tao Li, Yexi Jiang, Chunqiu Zeng, Bin Xia, Zheng Liu, Wubai Zhou, Xiaolong Zhu, Wentao Wang, Liang Zhang, Jun Wu, Li Xue, Dewei Bao:
FLAP: An End-to-End Event Log Analysis Platform for System Management. 1547-1556 - Shichen Liu, Fei Xiao, Wenwu Ou, Luo Si:
Cascade Ranking for Operational E-commerce Search. 1557-1565 - Quinten McNamara, Alejandro de la Vega
Developing a Comprehensive Framework for Multimodal Feature Extraction. 1567-1574 - Alejandro Mottini, Rodrigo Acuna-Agost:
Deep Choice Model Using Pointer Networks for Airline Itinerary Prediction. 1575-1583 - Debjyoti Paul, Feifei Li, Murali Krishna Teja, Xin Yu, Richie Frost:
Compass: Spatio Temporal Sentiment Analysis of US Election What Twitter Says! 1585-1594 - Rebecca S. Portnoff, Danny Yuxing Huang, Periwinkle Doerfler, Sadia Afroz, Damon McCoy:
Backpage and Bitcoin: Uncovering Human Traffickers. 1595-1604 - Paul Power, Héctor Ruiz, Xinyu Wei, Patrick Lucey:
Not All Passes Are Created Equal: Objectively Measuring the Risk and Reward of Passes in Soccer from Tracking Data. 1605-1613 - Xiao Qin, Tabassum Kakar, Susmitha Wunnava, Elke A. Rundensteiner, Lei Cao
MARAS: Signaling Multi-Drug Adverse Reactions. 1615-1623 - Parikshit Shah, Ming Yang, Sachidanand Alle, Adwait Ratnaparkhi, Ben Shahshahani, Rohit Chandra:
A Practical Exploration System for Search Advertising. 1625-1631 - Justin Sybrandt
MOLIERE: Automatic Biomedical Hypothesis Generation System. 1633-1642 - Sandeep Tata, Alexandrin Popescul, Marc Najork
Quick Access: Building a Smart Experience for Google Drive. 1643-1651 - Yongxin Tong
The Simpler The Better: A Unified Approach to Predicting Original Taxi Demands based on Large-Scale Online Platforms. 1653-1662 - Thomas Vandal, Evan Kodra, Sangram Ganguly, Andrew R. Michaelis, Ramakrishna R. Nemani, Auroop R. Ganguly:
DeepSD: Generating High Resolution Climate Change Projections through Single Image Super-Resolution. 1663-1672 - Jingyuan Wang, Chao Chen, Junjie Wu, Zhang Xiong:
No Longer Sleeping with a Bomb: A Duet System for Protecting Urban Safety from Dangerous Goods. 1673-1681 - Zhe Zhang
A Quasi-experimental Estimate of the Impact of P2P Transportation Platforms on Urban Consumer Patterns. 1683-1692 - Jun Zhou, Xiaolong Li
KunPeng: Parameter Server based Distributed Learning Systems and Its Applications in Alibaba and Ant Financial. 1693-1702 - Jie Zhu
Deep Embedding Forest: Forest-based Serving with Deep Embedding Features. 1703-1711
KDD 2017 Applied Data Science Papers (Poster Papers)
- Amr Ahmed, James Long, Daniel Silva, Yuan Wang:
A Practical Algorithm for Solving the Incoherence Problem of Topic Models In Industrial Applications. 1713-1721 - Blake Anderson, David A. McGrew:
Machine Learning for Encrypted Malware Traffic Classification: Accounting for Noisy Labels and Non-Stationarity. 1723-1732 - Albert Bifet
Extremely Fast Decision Tree Mining for Evolving Data Streams. 1733-1742 - Pedro Chahuara, Nicolas Grislain, Grégoire Jauvion, Jean-Michel Renders:
Real-Time Optimization of Web Publisher RTB Revenues. 1743-1751 - Benjamin Paul Chamberlain, Ângelo Cardoso, C. H. Bryan Liu, Roberto Pagliari, Marc Peter Deisenroth:
Customer Lifetime Value Prediction Using Embeddings. 1753-1762 - Heng-Tze Cheng, Zakaria Haque, Lichan Hong, Mustafa Ispir, Clemens Mewald, Illia Polosukhin, Georgios Roumpos, D. Sculley, Jamie Smith, David Soergel, Yuan Tang
TensorFlow Estimators: Managing Simplicity vs. Flexibility in High-Level Machine Learning Frameworks. 1763-1771 - Hamid Dadkhahi, Benjamin M. Marlin
Learning Tree-Structured Detection Cascades for Heterogeneous Networks of Embedded Devices. 1773-1781 - Supratim Deb, Zihui Ge, Sastry Isukapalli, Sarat C. Puthenpura, Shobha Venkataraman, He Yan, Jennifer Yates:
AESOP: Automatic Policy Learning for Predicting and Mitigating Network Service Impairments. 1783-1792 - Shalini Ghosh, Ariyam Das, Phillip A. Porras, Vinod Yegneswaran, Ashish Gehani:
Automated Categorization of Onion Sites for Analyzing the Darkweb Ecosystem. 1793-1802 - Naeemul Hassan
Toward Automated Fact-Checking: Detecting Check-worthy Factual Claims by ClaimBuster. 1803-1812 - Daniel N. Hill, Houssam Nassif, Yi Liu
An Efficient Bandit Algorithm for Realtime Multivariate Optimization. 1813-1821 - Vasileios Iosifidis, Eirini Ntoutsi:
Large Scale Sentiment Learning with Limited Labels. 1823-1832 - Shinji Ito, Ryohei Fujimaki:
Optimization Beyond Prediction: Prescriptive Price Optimization. 1833-1841 - Vijay Manikandan Janakiraman, Bryan L. Matthews, Nikunj C. Oza:
Finding Precursors to Anomalous Drop in Airspeed During a Flight's Takeoff. 1843-1852 - Brendan Kitts, Michael Krishnan, Ishadutta Yadav, Yongbo Zeng, Garrett Badeau, Andrew Potter, Sergey Tolkachov, Ethan Thornburg, Satyanarayana Reddy Janga:
Ad Serving with Multiple KPIs. 1853-1861 - Xiucheng Li, Yun Cheng, Gao Cong
Discovering Pollution Sources and Propagation Patterns in Urban Area. 1863-1872 - Keqian Li, Yeye He, Kris Ganjam:
Discovering Enterprise Concepts Using Spreadsheet Tables. 1873-1882 - Qiaoling Liu, Faizan Javed, Vachik S. Dave
Supporting Employer Name Normalization at both Entity and Cluster Level. 1883-1892 - Yin Lou, Mikhail Obukhov:
BDT: Gradient Boosted Decision Tables for High Accuracy and Scoring Efficiency. 1893-1901 - Fenglong Ma, Radha Chitta, Jing Zhou, Quanzeng You, Tong Sun, Jing Gao:
Dipole: Diagnosis Prediction in Healthcare via Attention-based Bidirectional Recurrent Neural Networks. 1903-1911 - Matthew Malloy, Paul Barford, Enis Ceyhun Alp, Jonathan Koller, Adria Jewell:
Internet Device Graphs. 1913-1921 - Emaad A. Manzoor, Leman Akoglu:
RUSH!: Targeted Time-limited Coupons via Purchase Forecasts. 1923-1931 - Shumpei Okura, Yukihiro Tagami, Shingo Ono, Akira Tajima:
Embedding-based News Recommendation for Millions of Users. 1933-1942 - Yaniv Ovadia, Yoni Halpern, Dilip Krishnan, Josh Livni, Daniel E. Newburger, Ryan Poplin, Tiantian Zha, D. Sculley:
Learning to Count Mosquitoes for the Sterile Insect Technique. 1943-1949 - Lujia Pan, Jianfeng Zhang, Patrick P. C. Lee
An Intelligent Customer Care Assistant System for Large-Scale Cellular Network Diagnosis. 1951-1959 - Yanxin Pan, Alexander Burnap, Jeffrey Hartley, Richard Gonzalez
Deep Design: Product Aesthetics for Heterogeneous Markets. 1961-1970 - Tom Quisel, Luca Foschini
Collecting and Analyzing Millions of mHealth Data Streams. 1971-1980 - Kosta Ristovski, Chetan Gupta, Kunihiko Harada, Hsiu-Khuern Tang:
Dispatch with Confidence: Integration of Machine Learning, Optimization and Simulation for Open Pit Mines. 1981-1989 - Héctor Ruiz, Paul Power, Xinyu Wei, Patrick Lucey:
"The Leicester City Fairytale?": Utilizing New Soccer Analytics Tools to Compare Performance in the 15/16 & 16/17 EPL Seasons. 1991-2000 - Hesam Salehian, Patrick D. Howell, Chul Lee:
Matching Restaurant Menus to Crowdsourced Food Data: A Scalable Machine Learning Approach. 2001-2009 - Ashlesh Sharma, Vidyuth Srinivasan, Vishal Kanchan, Lakshminarayanan Subramanian:
The Fake vs Real Goods Problem: Microscopy and Machine Learning to the Rescue. 2011-2019 - Kyle Soska, Christopher S. Gates, Kevin A. Roundy, Nicolas Christin
Automatic Application Identification from Billions of Files. 2021-2030 - Bin Tong, Martin Klinkigt, Makoto Iwayama, Toshihiko Yanase, Yoshiyuki Kobayashi, Anshuman Sahu, Ravigopal Vennelakanti:
Learning to Generate Rock Descriptions from Multivariate Well Logs with Hierarchical Attention. 2031-2040 - Toshimitsu Uesaka, Kai Morino, Hiroki Sugiura, Taichi Kiwaki, Hiroshi Murata, Ryo Asaoka, Kenji Yamanishi
Multi-view Learning over Retinal Thickness and Visual Sensitivity on Glaucomatous Eyes. 2041-2050 - Xuejian Wang, Lantao Yu, Kan Ren, Guanyu Tao, Weinan Zhang, Yong Yu, Jun Wang:
Dynamic Attention Deep Model for Article Recommendation by Learning Human Editors' Demonstration. 2051-2059 - Chenglong Wang, Feijun Jiang, Hongxia Yang:
A Hybrid Framework for Text Modeling with Convolutional RNN. 2061-2069 - Bronwyn Woods, David Adamson, Shayne Miel, Elijah Mayfield:
Formative Essay Feedback Using Predictive Scoring Models. 2071-2080 - Houping Xiao, Jing Gao, Long H. Vu, Deepak S. Turaga:
Learning Temporal State of Diabetes Patients via Combining Behavioral and Demographic Data. 2081-2089 - Hongxia Yang, Yada Zhu, Jingrui He:
Local Algorithm for User Action Prediction Towards Display Ads. 2091-2099 - Fan Yang, Ajinkya Kale, Yury Bubnov, Leon Stein, Qiaosong Wang
Visual Search at eBay. 2101-2110 - Sen Yang, Xin Dong, Leilei Sun
A Data-driven Process Recommender Framework. 2111-2120 - Emre Yilmaz, Sanem Elbasi, Hakan Ferhatosmanoglu:
Predicting Optimal Facility Location without Customer Locations. 2121-2130 - Zi Yin, Keng-hao Chang, Ruofei Zhang
DeepProbe: Information Directed Sequence Understanding and Chatbot Design via Recurrent Neural Networks. 2131-2139 - Liheng Zhang, Charu C. Aggarwal, Guo-Jun Qi
Stock Price Prediction via Discovering Multi-Frequency Trading Patterns. 2141-2149 - Lingyu Zhang, Tao Hu, Yue Min, Guobin Wu, Junying Zhang, Pengcheng Feng, Pinghua Gong, Jieping Ye:
A Taxi Order Dispatch Model based On Combinatorial Optimization. 2151-2159 - Guanjie Zheng, Susan L. Brantley, Thomas Lauvaux, Zhenhui Li:
Contextual Spatial Outlier Detection with Metric Learning. 2161-2170 - Kaiping Zheng, Jinyang Gao, Kee Yuan Ngiam
Resolving the Bias in Electronic Medical Records. 2171-2180 - Wubai Zhou, Wei Xue, Ramesh Baral, Qing Wang, Chunqiu Zeng, Tao Li, Jian Xu, Zheng Liu, Larisa Shwartz, Genady Ya. Grabarnik:
STAR: A System for Ticket Analysis and Resolution. 2181-2190 - Han Zhu, Junqi Jin, Chang Tan, Fei Pan, Yifan Zeng, Han Li, Kun Gai:
Optimized Cost per Click in Taobao Display Advertising. 2191-2200
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