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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, Zvi Lotker, Yinon Nahum, David Peleg:
Improved Degree Bounds and Full Spectrum Power Laws in Preferential Attachment Networks. 45-53 - Zilong Bai, Peter B. Walker, Anna E. Tschiffely, Fei Wang, Ian Davidson:
Unsupervised Network Discovery for Brain Imaging Data. 55-64 - Inci M. Baytas, Cao Xiao, Xi Zhang, Fei Wang, Anil K. Jain, Jiayu Zhou:
Patient Subtyping via Time-Aware LSTM Networks. 65-74 - Xiaojun Chang, Yaoliang Yu, Yi Yang:
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, Caterina Mordente, Maurizio Patrignani, Riccardo Torlone:
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, Ananthram Swami:
metapath2vec: Scalable Representation Learning for Heterogeneous Networks. 135-144 - Alessandro Epasto, Silvio Lattanzi, Renato Paes Leme:
Ego-Splitting Framework: from Non-Overlapping to Overlapping Clusters. 145-154 - Ian Fox, Lynn Ang, Mamta Jaiswal, Rodica Pop-Busui, Jenna Wiens:
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, Zhiting Hu, Taylor Berg-Kirkpatrick, Ying Huang, Eric P. Xing:
Efficient Correlated Topic Modeling with Topic Embedding. 225-233 - Tom Hope, Joel Chan, Aniket Kittur, Dafna Shahaf:
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, Shiqiang Yang:
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, Yong Wang, Conglei Shi, Nan Cao, Norbou Buchler:
Is the Whole Greater Than the Sum of Its Parts? 295-304 - Xiaopeng Li, James She:
Collaborative Variational Autoencoder for Recommender Systems. 305-314 - Ping Li:
Linearized GMM Kernels and Normalized Random Fourier Features. 315-324 - Defu Lian, Rui Liu, Yong Ge, Kai Zheng, Xing Xie, Longbing Cao:
Discrete Content-aware Matrix Factorization. 325-334 - Junming Liu, Yanjie Fu, Jingci Ming, Yong Ren, Leilei Sun, Hui Xiong:
Effective and Real-time In-App Activity Analysis in Encrypted Internet Traffic Streams. 335-344 - Tingjin Luo, Weizhong Zhang, Shang Qiu, Yang Yang, Dongyun Yi, Guangtao Wang, Jieping Ye, Jie Wang:
Functional Annotation of Human Protein Coding Isoforms via Non-convex Multi-Instance Learning. 345-354 - Panagiotis Mandros, Mario Boley, Jilles Vreeken:
Discovering Reliable Approximate Functional Dependencies. 355-363 - Dominik Mautz, Wei Ye, Claudia Plant, Christian Böhm:
Towards an Optimal Subspace for K-Means. 365-373 - Ioakeim Perros, Evangelos E. Papalexakis, Fei Wang, Richard W. Vuduc, Elizabeth Searles, Michael Thompson, Jimeng Sun:
SPARTan: Scalable PARAFAC2 for Large & Sparse Data. 375-384 - Leonardo Filipe Rodrigues Ribeiro, Pedro H. P. Saverese, Daniel R. Figueiredo:
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, Hong-Han Shuai, Wang-Chien Lee, Ming-Syan Chen:
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, Hancheng Ge, James Caverlee, Xia Hu:
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, Andrew Haines, Mounia Lalmas:
Interpretable Predictions of Tree-based Ensembles via Actionable Feature Tweaking. 465-474 - Shen Wang, Lifang He, Bokai Cao, Chun-Ta Lu, Philip S. Yu, Ann B. Ragin:
Structural Deep Brain Network Mining. 475-484 - Suhang Wang, Charu C. Aggarwal, Huan Liu:
Randomized Feature Engineering as a Fast and Accurate Alternative to Kernel Methods. 485-494 - Pengfei Wang, Yanjie Fu, Guannan Liu, Wenqing Hu, Charu C. Aggarwal:
Human Mobility Synchronization and Trip Purpose Detection with Mixture of Hawkes Processes. 495-503 - Sibo Wang, Renchi Yang, Xiaokui Xiao, Zhewei Wei, Yin Yang:
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, Xianping Tao, Jian Lu:
HoORaYs: High-order Optimization of Rating Distance for Recommender Systems. 525-534 - Guangxu Xun, Yaliang Li, Jing Gao, Aidong Zhang:
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, Peng Cui, Christos Faloutsos, Wenwu Zhu:
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, Liyuan Liu, Dongming Lei, Quan Yuan, Honglei Zhuang, Tim Hanratty, Jiawei Han:
TrioVecEvent: Embedding-Based Online Local Event Detection in Geo-Tagged Tweet Streams. 595-604 - Chenzi Zhang, Fan Wei, Qin Liu, Zhihao Gavin Tang, Zhenguo Li:
Graph Edge Partitioning via Neighborhood Heuristic. 605-614 - Kai Zhang, Chuanren Liu, Jie Zhang, Hui Xiong, Eric P. Xing, Jieping Ye:
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, Hasan Davulcu, Jingrui He:
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, Snigdhansu Chatterjee, Vipin Kumar:
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, Bing Liu, Alexander Tuzhilin:
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, Olu Ajilore, Kelly Ryan, Alex D. Leow:
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, Mohammad Taha Bahadori, Le Song, Walter F. Stewart, Jimeng Sun:
GRAM: Graph-based Attention Model for Healthcare Representation Learning. 787-795 - Sam Corbett-Davies, Emma Pierson, Avi Feller, Sharad Goel, Aziz Huq:
Algorithmic Decision Making and the Cost of Fairness. 797-806 - Yuxiao Dong, Reid A. Johnson, Jian Xu, Nitesh V. Chawla:
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, Keivan Alizadeh, Ali Khodadadi, Ali Arabzadeh, Mehrdad Farajtabar, Hongyuan Zha, Hamid R. Rabiee:
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, James Gerber, Kimberly Carlson, Paul C. West, Vipin Kumar:
Incremental Dual-memory LSTM in Land Cover Prediction. 867-876 - Meng Jiang, Jingbo Shang, Taylor Cassidy, Xiang Ren, Lance M. Kaplan, Timothy P. Hanratty, Jiawei Han:
MetaPAD: Meta Pattern Discovery from Massive Text Corpora. 877-886 - Yejin Kim, Jimeng Sun, Hwanjo Yu, Xiaoqian Jiang:
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, Daqing He:
Semi-Supervised Techniques for Mining Learning Outcomes and Prerequisites. 907-915 - Huayu Li, Yong Ge, Hengshu Zhu, Hui Xiong, Hongke Zhao:
Prospecting the Career Development of Talents: A Survival Analysis Perspective. 917-925 - Huayu Li, Martin Renqiang Min, Yong Ge, Asim Kadav:
A Context-aware Attention Network for Interactive Question Answering. 927-935 - Sulin Liu, Sinno Jialin Pan, Qirong Ho:
Distributed Multi-Task Relationship Learning. 937-946 - Yanchi Liu, Chuanren Liu, Xinjiang Lu, Mingfei Teng, Hengshu Zhu, Hui Xiong:
Point-of-Interest Demand Modeling with Human Mobility Patterns. 947-955 - Junming Liu, Leilei Sun, Qiao Li, Jingci Ming, Yanchi Liu, Hui Xiong:
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, Jiliang Tang, Jingdong Wang, Jiebo Luo:
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, Charles K. Nicholas:
An Alternative to NCD for Large Sequences, Lempel-Ziv Jaccard Distance. 1007-1015 - Polina Rozenshtein, Nikolaj Tatti, Aristides Gionis:
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