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ORCID22nd KDD 2016: San Francisco, CA, USA
- Balaji Krishnapuram, Mohak Shah, Alexander J. Smola, Charu C. Aggarwal, Dou Shen, Rajeev Rastogi:
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Francisco, CA, USA, August 13-17, 2016. ACM 2016, ISBN 978-1-4503-4232-2
Keynote Talks
- Jennifer T. Chayes:
Graphons and Machine Learning: Modeling and Estimation of Sparse Massive Networks. 1 - Nando de Freitas:
Learning to Learn and Compositionality with Deep Recurrent Neural Networks: Learning to Learn and Compositionality. 3 - Whitfield Diffie:
The Evolving Meaning of Information Security. 5 - Joseph M. Hellerstein:
People, Computers, and The Hot Mess of Real Data. 7 - Greg Papadopoulos:
A VC View of Investing in ML. 9
Panel
- Evangelos Simoudis, Mark Gorenberg, Tim Guleri, Matt Ocko, Greg Sands:
Big Data Needs Big Dreamers: Lessons from Successful Big Data Investors. 11-12
Applied Data Science Track Full Papers
- Klaus Ackermann
, Eduardo Blancas Reyes, Sue He, Thomas Anderson Keller, Paul van der Boor, Romana Khan, Rayid Ghani, José Carlos González:
Designing Policy Recommendations to Reduce Home Abandonment in Mexico. 13-20 - Samet Ayhan, Hanan Samet:
Aircraft Trajectory Prediction Made Easy with Predictive Analytics. 21-30 - Reza Bosagh Zadeh, Xiangrui Meng, Alexander Ulanov, Burak Yavuz, Li Pu, Shivaram Venkataraman, Evan Randall Sparks, Aaron Staple, Matei Zaharia:
Matrix Computations and Optimization in Apache Spark. 31-38 - Mirela Madalina Botezatu, Ioana Giurgiu, Jasmina Bogojeska, Dorothea Wiesmann:
Predicting Disk Replacement towards Reliable Data Centers. 39-48 - Joel Brooks, Matthew Kerr, John V. Guttag:
Developing a Data-Driven Player Ranking in Soccer Using Predictive Model Weights. 49-55 - Matthew Burgess, Eugenia Giraudy, Julian Katz-Samuels, Joe Walsh, Derek Willis, Lauren Haynes, Rayid Ghani:
The Legislative Influence Detector: Finding Text Reuse in State Legislation. 57-66 - Samuel Carton, Jennifer Helsby, Kenneth Joseph, Ayesha Mahmud, Youngsoo Park, Joe Walsh, Crystal Cody, C. P. T. Estella Patterson, Lauren Haynes, Rayid Ghani:
Identifying Police Officers at Risk of Adverse Events. 67-76 - Alex Deng, Xiaolin Shi:
Data-Driven Metric Development for Online Controlled Experiments: Seven Lessons Learned. 77-86 - Bowen Du, Chuanren Liu, Wenjun Zhou, Zhenshan Hou, Hui Xiong:
Catch Me If You Can: Detecting Pickpocket Suspects from Large-Scale Transit Records. 87-96 - Rupesh Gupta, Guanfeng Liang, Hsiao-Ping Tseng, Ravi Kiran Holur Vijay, Xiaoyu Chen, Rómer Rosales:
Email Volume Optimization at LinkedIn. 97-106 - JungWoo Ha, Hyuna Pyo, Jeonghee Kim:
Large-Scale Item Categorization in e-Commerce Using Multiple Recurrent Neural Networks. 107-115 - Jim C. Huang, Rodolphe Jenatton, Cédric Archambeau:
Online Dual Decomposition for Performance and Delivery-Based Distributed Ad Allocation. 117-126 - Bo Jin, Chao Che, Kuifei Yu, Yue Qu, Li Guo, Cuili Yao, Ruiyun Yu, Qiang Zhang:
Minimizing Legal Exposure of High-Tech Companies through Collaborative Filtering Methods. 127-136 - Navneet Kapur, Nikita I. Lytkin, Bee-Chung Chen, Deepak Agarwal, Igor Perisic:
Ranking Universities Based on Career Outcomes of Graduates. 137-144 - Muhammad Raza Khan, Joshua E. Blumenstock:
Predictors without Borders: Behavioral Modeling of Product Adoption in Three Developing Countries. 145-154 - Guimei Liu, Tam T. Nguyen, Gang Zhao, Wei Zha, Jianbo Yang, Jianneng Cao, Min Wu, Peilin Zhao, Wei Chen:
Repeat Buyer Prediction for E-Commerce. 155-164 - Haishan Liu, David Pardoe, Kun Liu, Manoj Thakur, Frank Cao, Chongzhe Li:
Audience Expansion for Online Social Network Advertising. 165-174 - Ping Luo, Su Yan, Zhiqiang Liu, Zhiyong Shen, Shengwen Yang, Qing He:
From Online Behaviors to Offline Retailing. 175-184 - Michael A. Madaio, Shang-Tse Chen, Oliver L. Haimson, Wenwen Zhang, Xiang Cheng, Matthew Hinds-Aldrich, Duen Horng Chau, Bistra Dilkina:
Firebird: Predicting Fire Risk and Prioritizing Fire Inspections in Atlanta. 185-194 - Eric Malmi, Pyry Takala, Hannu Toivonen, Tapani Raiko, Aristides Gionis:
DopeLearning: A Computational Approach to Rap Lyrics Generation. 195-204 - Sathappan Muthiah, Patrick Butler, Rupinder Paul Khandpur, Parang Saraf, Nathan Self, Alla Rozovskaya, Liang Zhao, Jose Cadena, Chang-Tien Lu, Anil Vullikanti, Achla Marathe, Kristen Maria Summers, Graham Katz, Andy Doyle, Jaime Arredondo, Dipak K. Gupta, David Mares, Naren Ramakrishnan:
EMBERS at 4 years: Experiences operating an Open Source Indicators Forecasting System. 205-214 - Animesh Nandi, Atri Mandal, Shubham Atreja, Gargi Banerjee Dasgupta, Subhrajit Bhattacharya:
Anomaly Detection Using Program Control Flow Graph Mining From Execution Logs. 215-224 - Alexander G. Nikolaev, Shounak Gore, Venu Govindaraju:
Engagement Capacity and Engaging Team Formation for Reach Maximization of Online Social Media Platforms. 225-234 - Alexey Poyarkov, Alexey Drutsa, Andrey Khalyavin, Gleb Gusev, Pavel Serdyukov:
Boosted Decision Tree Regression Adjustment for Variance Reduction in Online Controlled Experiments. 235-244 - Mahsa Salehi, Laura Irina Rusu, Timothy M. Lynar, Anna Phan:
Dynamic and Robust Wildfire Risk Prediction System: An Unsupervised Approach. 245-254 - Ying Shan, T. Ryan Hoens, Jian Jiao, Haijing Wang, Dong Yu, J. C. Mao:
Deep Crossing: Web-Scale Modeling without Manually Crafted Combinatorial Features. 255-262 - Gursimran Singh, Shashank Srikant, Varun Aggarwal:
Question Independent Grading using Machine Learning: The Case of Computer Program Grading. 263-272 - Yu Sun, Nicholas Jing Yuan, Yingzi Wang, Xing Xie, Kieran McDonald, Rui Zhang:
Contextual Intent Tracking for Personal Assistants. 273-282 - Liang Tang, Bo Long, Bee-Chung Chen, Deepak Agarwal:
An Empirical Study on Recommendation with Multiple Types of Feedback. 283-292 - Ali Vanderveld, Addhyan Pandey, Angela Han, Rajesh Parekh:
An Engagement-Based Customer Lifetime Value System for E-commerce. 293-302 - Ellery Wulczyn, Madian Khabsa, Vrushank Vora, Matthew Heston, Joe Walsh, Christopher Berry, Rayid Ghani:
Identifying Earmarks in Congressional Bills. 303-311 - Ya Xu, Nanyu Chen:
Evaluating Mobile Apps with A/B and Quasi A/B Tests. 313-322 - Dawei Yin, Yuening Hu, Jiliang Tang, Tim Daly Jr., Mianwei Zhou, Hua Ouyang, Jianhui Chen, Changsung Kang, Hongbo Deng, Chikashi Nobata, Jean-Marc Langlois, Yi Chang:
Ranking Relevance in Yahoo Search. 323-332 - Shipeng Yu, Evangelia Christakopoulou, Abhishek Gupta:
Identifying Decision Makers from Professional Social Networks. 333-342 - Qingqi Yue, Ao Yuan, Xuan Che, Minh Huynh, Chunxiao Zhou:
Batch Model for Batched Timestamps Data Analysis with Application to the SSA Disability Program. 343-352 - Fuzheng Zhang, Nicholas Jing Yuan, Defu Lian, Xing Xie, Wei-Ying Ma:
Collaborative Knowledge Base Embedding for Recommender Systems. 353-362 - XianXing Zhang, Yitong Zhou, Yiming Ma, Bee-Chung Chen, Liang Zhang, Deepak Agarwal:
GLMix: Generalized Linear Mixed Models For Large-Scale Response Prediction. 363-372 - Yijun Zhao, Bilal Ahmed, Thomas Thesen, Karen E. Blackmon, Jennifer G. Dy, Carla E. Brodley, Ruben Kuzniecky, Orrin Devinsky:
A Non-parametric Approach to Detect Epileptogenic Lesions using Restricted Boltzmann Machines. 373-382 - Chen Zhu, Hengshu Zhu, Hui Xiong, Pengliang Ding, Fang Xie:
Recruitment Market Trend Analysis with Sequential Latent Variable Models. 383-392 - Hengshu Zhu, Hui Xiong, Fangshuang Tang, Qi Liu, Yong Ge, Enhong Chen, Yanjie Fu:
Days on Market: Measuring Liquidity in Real Estate Markets. 393-402
Applied Data Science Track Invited Talks
- Jonathan D. Becher:
Can You Teach the Elephant to Dance? AKA: Culture Eats Data Science for Breakfast. 403 - Oliver Downs:
How Machine Learning has Finally Solved Wanamaker's Dilemma. 405 - Ralf Herbrich:
Learning Sparse Models at Scale. 407 - Ching Law:
Profiling Users from Online Social Behaviors with Applications for Tencent Social Ads. 409 - Ingo Mierswa:
The Wisdom of Crowds: Best Practices for Data Prep & Machine Learning Derived from Millions of Data Science Workflows. 411 - Jeff Schneider:
Bayesian Optimization and Embedded Learning Systems. 413 - Danny Shapiro:
Accelerating the Race to Autonomous Cars. 415 - Ashok Srivastava:
Large-Scale Machine Learning at Verizon: Theory and Applications. 417 - Duncan J. Watts:
Computational Social Science: Exciting Progress and Future Challenges. 419
Applied Data Science Track Posters
- Bo An, Haipeng Chen, Noseong Park, V. S. Subrahmanian:
MAP: Frequency-Based Maximization of Airline Profits based on an Ensemble Forecasting Approach. 421-430 - Nipun Batra, Amarjeet Singh, Kamin Whitehouse:
Gemello: Creating a Detailed Energy Breakdown from Just the Monthly Electricity Bill. 431-440 - Fedor Borisyuk, Krishnaram Kenthapadi, David Stein, Bo Zhao:
CaSMoS: A Framework for Learning Candidate Selection Models over Structured Queries and Documents. 441-450 - Boris Chidlovskii, Stéphane Clinchant, Gabriela Csurka:
Domain Adaptation in the Absence of Source Domain Data. 451-460 - Steven H. H. Ding, Benjamin C. M. Fung, Philippe Charland:
Kam1n0: MapReduce-based Assembly Clone Search for Reverse Engineering. 461-470 - Sahin Cem Geyik, Sergey Faleev, Jianqiang Shen, Sean O'Donnell, Santanu Kolay:
Joint Optimization of Multiple Performance Metrics in Online Video Advertising. 471-480 - Xiaoxiao Guo, Wei Li, Francesco Iorio:
Convolutional Neural Networks for Steady Flow Approximation. 481-490 - Zhaobin Kuang, James A. Thomson, Michael Caldwell, Peggy L. Peissig, Ron M. Stewart, David Page:
Computational Drug Repositioning Using Continuous Self-Controlled Case Series. 491-500 - Jia Li, Dhruv Arya, Viet Ha-Thuc, Shakti Sinha:
How to Get Them a Dream Job?: Entity-Aware Features for Personalized Job Search Ranking. 501-510 - Xiang Li, Milad Makkie, Binbin Lin, Mojtaba Sedigh Fazli, Ian Davidson, Jieping Ye, Tianming Liu, Shannon Quinn:
Scalable Fast Rank-1 Dictionary Learning for fMRI Big Data Analysis. 511-519 - Qiaoling Liu, Faizan Javed, Matt McNair:
CompanyDepot: Employer Name Normalization in the Online Recruitment Industry. 521-530 - Caroline Lo, Dan Frankowski, Jure Leskovec:
Understanding Behaviors that Lead to Purchasing: A Case Study of Pinterest. 531-540 - Corey Lynch, Kamelia Aryafar, Josh Attenberg:
Images Don't Lie: Transferring Deep Visual Semantic Features to Large-Scale Multimodal Learning to Rank. 541-548 - Hoang Nguyen, Jon D. Patrick:
Text Mining in Clinical Domain: Dealing with Noise. 549-558 - John Paparrizos, Ryen W. White, Eric Horvitz:
Detecting Devastating Diseases in Search Logs. 559-568 - Bryan Perozzi, Michael Schueppert, Jack Saalweachter, Mayur Thakur:
When Recommendation Goes Wrong: Anomalous Link Discovery in Recommendation Networks. 569-578 - Jim Pivarski, Collin Bennett, Robert L. Grossman:
Deploying Analytics with the Portable Format for Analytics (PFA). 579-588 - Hasan Poonawala, Vinay Kolar, Sebastien Blandin, Laura Wynter, Sambit Sahu:
Singapore in Motion: Insights on Public Transport Service Level Through Farecard and Mobile Data Analytics. 589-598 - Parang Saraf, Naren Ramakrishnan:
EMBERS AutoGSR: Automated Coding of Civil Unrest Events. 599-608 - Taraneh Taghavi, Maria Lupetini, Yaron Kretchmer:
Compute Job Memory Recommender System Using Machine Learning. 609-616 - Yinyan Tan, Zhe Fan, Guilin Li, Fangshan Wang, Zhengbing Li, Shikai Liu, Qiuling Pan, Eric P. Xing, Qirong Ho:
Scalable Time-Decaying Adaptive Prediction Algorithm. 617-626 - Jan Van Haaren, Horesh Ben Shitrit, Jesse Davis, Pascal Fua:
Analyzing Volleyball Match Data from the 2014 World Championships Using Machine Learning Techniques. 627-634 - Hongjian Wang, Daniel Kifer, Corina Graif, Zhenhui Li:
Crime Rate Inference with Big Data. 635-644 - Huizhi Xie, Juliette Aurisset:
Improving the Sensitivity of Online Controlled Experiments: Case Studies at Netflix. 645-654 - Huang Xu, Zhiwen Yu, Jingyuan Yang, Hui Xiong, Hengshu Zhu:
Talent Circle Detection in Job Transition Networks. 655-664 - Weinan Zhang, Tianxiong Zhou, Jun Wang, Jian Xu:
Bid-aware Gradient Descent for Unbiased Learning with Censored Data in Display Advertising. 665-674
Research Track Full Papers
- Takuya Akiba, Yosuke Yano:
Compact and Scalable Graph Neighborhood Sketching. 685-694 - Hesam Amoualian, Marianne Clausel, Éric Gaussier, Massih-Reza Amini:
Streaming-LDA: A Copula-based Approach to Modeling Topic Dependencies in Document Streams. 695-704 - Ashton Anderson, Jon M. Kleinberg, Sendhil Mullainathan:
Assessing Human Error Against a Benchmark of Perfection. 705-714 - David T. Arbour, Dan Garant, David D. Jensen:
Inferring Network Effects from Observational Data. 715-724 - Maria-Florina Balcan, Yingyu Liang, Le Song, David P. Woodruff, Bo Xie:
Communication Efficient Distributed Kernel Principal Component Analysis. 725-734 - Roel Bertens, Jilles Vreeken, Arno Siebes:
Keeping it Short and Simple: Summarising Complex Event Sequences with Multivariate Patterns. 735-744 - Marco Bressan, Stefano Leucci, Alessandro Panconesi, Prabhakar Raghavan, Erisa Terolli:
The Limits of Popularity-Based Recommendations, and the Role of Social Ties. 745-754 - Shiyu Chang, Yang Zhang, Jiliang Tang, Dawei Yin, Yi Chang, Mark A. Hasegawa-Johnson, Thomas S. Huang:
Positive-Unlabeled Learning in Streaming Networks. 755-764 - Chen Chen, Hanghang Tong, Lei Xie, Lei Ying, Qing He:
FASCINATE: Fast Cross-Layer Dependency Inference on Multi-layered Networks. 765-774 - Shuo Chen, Thorsten Joachims:
Predicting Matchups and Preferences in Context. 775-784 - Tianqi Chen, Carlos Guestrin:
XGBoost: A Scalable Tree Boosting System. 785-794 - Wei Chen, Tian Lin, Zihan Tan, Mingfei Zhao, Xuren Zhou:
Robust Influence Maximization. 795-804 - Wei Cheng, Kai Zhang, Haifeng Chen, Guofei Jiang, Zhengzhang Chen, Wei Wang:
Ranking Causal Anomalies via Temporal and Dynamical Analysis on Vanishing Correlations. 805-814 - Konstantina Christakopoulou, Filip Radlinski, Katja Hofmann:
Towards Conversational Recommender Systems. 815-824 - Lorenzo De Stefani, Alessandro Epasto, Matteo Riondato, Eli Upfal:
TRIÈST: Counting Local and Global Triangles in Fully-Dynamic Streams with Fixed Memory Size. 825-834 - Jaroslav M. Fowkes, Charles Sutton:
A Subsequence Interleaving Model for Sequential Pattern Mining. 835-844 - Mina Ghashami, Edo Liberty, Jeff M. Phillips:
Efficient Frequent Directions Algorithm for Sparse Matrices. 845-854 - Aditya Grover, Jure Leskovec:
node2vec: Scalable Feature Learning for Networks. 855-864 - Lei Han, Yu Zhang, Xiu-Feng Wan, Tong Zhang:
Generalized Hierarchical Sparse Model for Arbitrary-Order Interactive Antigenic Sites Identification in Flu Virus Data. 865-874 - Lifang He, Chun-Ta Lu, Jiaqi Ma, Jianping Cao, Linlin Shen, Philip S. Yu:
Joint Community and Structural Hole Spanner Detection via Harmonic Modularity. 875-884 - Xinran He, David Kempe:
Robust Influence Maximization. 885-894 - Bryan Hooi, Hyun Ah Song, Alex Beutel, Neil Shah, Kijung Shin, Christos Faloutsos:
FRAUDAR: Bounding Graph Fraud in the Face of Camouflage. 895-904 - Hao Hu, Joey Velez-Ginorio, Guo-Jun Qi:
Temporal Order-based First-Take-All Hashing for Fast Attention-Deficit-Hyperactive-Disorder Detection. 905-914 - Hui-Ju Hung, Hong-Han Shuai, De-Nian Yang, Liang-Hao Huang, Wang-Chien Lee, Jian Pei, Ming-Syan Chen:
When Social Influence Meets Item Inference. 915-924 - Arun Shankar Iyer, J. Saketha Nath, Sunita Sarawagi:
Privacy-preserving Class Ratio Estimation. 925-934 - Himanshu Jain, Yashoteja Prabhu, Manik Varma:
Extreme Multi-label Loss Functions for Recommendation, Tagging, Ranking & Other Missing Label Applications. 935-944 - Meng Jiang, Christos Faloutsos, Jiawei Han:
CatchTartan: Representing and Summarizing Dynamic Multicontextual Behaviors. 945-954 - Anjuli Kannan, Karol Kurach, Sujith Ravi, Tobias Kaufmann, Andrew Tomkins, Balint Miklos, Greg Corrado, László Lukács, Marina Ganea, Peter Young, Vivek Ramavajjala:
Smart Reply: Automated Response Suggestion for Email. 955-964 - Florian Lemmerich, Martin Becker, Philipp Singer, Denis Helic, Andreas Hotho, Markus Strohmaier:
Mining Subgroups with Exceptional Transition Behavior. 965-974 - Huayu Li, Yong Ge, Richang Hong, Hengshu Zhu:
Point-of-Interest Recommendations: Learning Potential Check-ins from Friends. 975-984 - Liangyue Li, Yuan Yao, Jie Tang, Wei Fan, Hanghang Tong:
QUINT: On Query-Specific Optimal Networks. 985-994 - Shangsong Liang, Emine Yilmaz, Evangelos Kanoulas:
Dynamic Clustering of Streaming Short Documents. 995-1004 - Junming Liu, Leilei Sun, Weiwei Chen, Hui Xiong:
Rebalancing Bike Sharing Systems: A Multi-source Data Smart Optimization. 1005-1014 - Yanchi Liu, Chuanren Liu, Bin Liu, Meng Qu, Hui Xiong:
Unified Point-of-Interest Recommendation with Temporal Interval Assessment. 1015-1024 - Son T. Mai, Ira Assent, Martin Storgaard:
AnyDBC: An Efficient Anytime Density-based Clustering Algorithm for Very Large Complex Datasets. 1025-1034 - Emaad A. Manzoor, Sadegh M. Milajerdi, Leman Akoglu:
Fast Memory-efficient Anomaly Detection in Streaming Heterogeneous Graphs. 1035-1044 - Yasuko Matsubara, Yasushi Sakurai:
Regime Shifts in Streams: Real-time Forecasting of Co-evolving Time Sequences. 1045-1054 - Samuel Maurus, Claudia Plant:
Skinny-dip: Clustering in a Sea of Noise. 1055-1064 - Igor Melnyk, Arindam Banerjee, Bryan L. Matthews, Nikunj C. Oza:
Semi-Markov Switching Vector Autoregressive Model-Based Anomaly Detection in Aviation Systems. 1065-1074 - Subhabrata Mukherjee, Stephan Günnemann, Gerhard Weikum:
Continuous Experience-aware Language Model. 1075-1084 - Sharad Nandanwar, M. Narasimha Murty:
Structural Neighborhood Based Classification of Nodes in a Network. 1085-1094 - Yue Ning, Sathappan Muthiah, Huzefa Rangwala, Naren Ramakrishnan:
Modeling Precursors for Event Forecasting via Nested Multi-Instance Learning. 1095-1104 - Mingdong Ou, Peng Cui, Jian Pei, Ziwei Zhang, Wenwu Zhu:
Asymmetric Transitivity Preserving Graph Embedding. 1105-1114 - Ha-Myung Park, Sung-Hyon Myaeng, U Kang:
PTE: Enumerating Trillion Triangles On Distributed Systems. 1115-1124 - Steffen Rendle, Dennis Fetterly, Eugene J. Shekita, Bor-Yiing Su:
Robust Large-Scale Machine Learning in the Cloud. 1125-1134 - Marco Túlio Ribeiro, Sameer Singh, Carlos Guestrin:
"Why Should I Trust You?": Explaining the Predictions of Any Classifier. 1135-1144 - Matteo Riondato, Eli Upfal:
ABRA: Approximating Betweenness Centrality in Static and Dynamic Graphs with Rademacher Averages. 1145-1154 - Pablo Robles-Granda, Sebastián Moreno, Jennifer Neville:
Sampling of Attributed Networks from Hierarchical Generative Models. 1155-1164 - Si Si, Kai-Yang Chiang, Cho-Jui Hsieh, Nikhil Rao, Inderjit S. Dhillon:
Goal-Directed Inductive Matrix Completion. 1165-1174 - Arlei Silva, Xuan-Hong Dang, Prithwish Basu, Ambuj K. Singh, Ananthram Swami:
Graph Wavelets via Sparse Cuts. 1175-1184 - Payam Siyari, Bistra Dilkina, Constantine Dovrolis:
Lexis: An Optimization Framework for Discovering the Hierarchical Structure of Sequential Data. 1185-1194 - Daniel Ting:
Towards Optimal Cardinality Estimation of Unions and Intersections with Sketches. 1195-1204 - Kai Ming Ting, Ye Zhu, Mark James Carman, Yue Zhu, Zhi-Hua Zhou:
Overcoming Key Weaknesses of Distance-based Neighbourhood Methods using a Data Dependent Dissimilarity Measure. 1205-1214 - William Trouleau, Azin Ashkan, Weicong Ding, Brian Eriksson:
Just One More: Modeling Binge Watching Behavior. 1215-1224 - Daixin Wang, Peng Cui, Wenwu Zhu:
Structural Deep Network Embedding. 1225-1234 - Shuai Wang, Zhiyuan Chen, Geli Fei, Bing Liu, Sherry Emery:
Targeted Topic Modeling for Focused Analysis. 1235-1244 - Xiaoqian Wang, Feiping Nie, Heng Huang:
Structured Doubly Stochastic Matrix for Graph Based Clustering: Structured Doubly Stochastic Matrix. 1245-1254 - Geoffrey I. Webb, François Petitjean:
A Multiple Test Correction for Streams and Cascades of Statistical Hypothesis Tests. 1255-1264 - Lingfei Wu, Ian En-Hsu Yen, Jie Chen, Rui Yan:
Revisiting Random Binning Features: Fast Convergence and Strong Parallelizability. 1265-1274 - Chang Xu, Dacheng Tao, Chao Xu:
Robust Extreme Multi-label Learning. 1275-1284 - Tong Xu, Hengshu Zhu, Xiangyu Zhao, Qi Liu, Hao Zhong, Enhong Chen, Hui Xiong:
Taxi Driving Behavior Analysis in Latent Vehicle-to-Vehicle Networks: A Social Influence Perspective. 1285-1294 - Shuangfei Zhai, Keng-hao Chang, Ruofei Zhang, Zhongfei (Mark) Zhang:
DeepIntent: Learning Attentions for Online Advertising with Recurrent Neural Networks. 1295-1304 - Chao Zhang, Keyang Zhang, Quan Yuan, Luming Zhang, Tim Hanratty, Jiawei Han:
GMove: Group-Level Mobility Modeling Using Geo-Tagged Social Media. 1305-1314 - Hongyang Zhang, Peter Lofgren, Ashish Goel:
Approximate Personalized PageRank on Dynamic Graphs. 1315-1324 - Kai Zhang, Shandian Zhe, Chaoran Cheng, Zhi Wei, Zhengzhang Chen, Haifeng Chen, Guofei Jiang, Yuan Qi, Jieping Ye:
Annealed Sparsity via Adaptive and Dynamic Shrinking. 1325-1334 - Min-Ling Zhang, Bin-Bin Zhou, Xu-Ying Liu:
Partial Label Learning via Feature-Aware Disambiguation. 1335-1344 - Si Zhang, Hanghang Tong:
FINAL: Fast Attributed Network Alignment. 1345-1354 - Tianyang Zhang, Peng Cui, Christos Faloutsos, Yunfei Lu, Hao Ye, Wenwu Zhu, Shiqiang Yang:
Come-and-Go Patterns of Group Evolution: A Dynamic Model. 1355-1364 - Yizhou Zhang, Yun Xiong, Xiangnan Kong, Yangyong Zhu:
NetCycle: Collective Evolution Inference in Heterogeneous Information Networks. 1365-1374 - Shuo Zhou, Xuan Vinh Nguyen, James Bailey, Yunzhe Jia, Ian Davidson:
Accelerating Online CP Decompositions for Higher Order Tensors. 1375-1384
Research Track Posters
- Miguel Angel Alcobendas Lisbona, Sheide Chammas, Kuang-chih Lee:
Optimal Reserve Prices in Upstream Auctions: Empirical Application on Online Video Advertising. 1395-1404 - Rodrigo Augusto da Silva Alves, Renato Martins Assunção, Pedro Olmo Stancioli Vaz de Melo:
Burstiness Scale: A Parsimonious Model for Characterizing Random Series of Events. 1405-1414 - Prithu Banerjee, Pranali Yawalkar, Sayan Ranu:
MANTRA: A Scalable Approach to Mining Temporally Anomalous Sub-trajectories. 1415-1424 - Yanan Bao, Huasen Wu, Xin Liu:
From Prediction to Action: A Closed-Loop Approach for Data-Guided Network Resource Allocation. 1425-1434 - Giorgos Borboudakis, Ioannis Tsamardinos:
Towards Robust and Versatile Causal Discovery for Business Applications. 1435-1444 - Yue Cao, Mingsheng Long, Jianmin Wang, Qiang Yang, Philip S. Yu:
Deep Visual-Semantic Hashing for Cross-Modal Retrieval. 1445-1454 - Sunandan Chakraborty, Ashwin Venkataraman, Srikanth Jagabathula, Lakshminarayanan Subramanian:
Predicting Socio-Economic Indicators using News Events. 1455-1464 - Chen Chen, Cewu Lu, Qixing Huang, Qiang Yang, Dimitrios Gunopulos, Leonidas J. Guibas:
City-Scale Map Creation and Updating using GPS Collections. 1465-1474 - Wenlin Chen, James T. Wilson, Stephen Tyree, Kilian Q. Weinberger, Yixin Chen:
Compressing Convolutional Neural Networks in the Frequency Domain. 1475-1484 - Wei-Lin Chiang, Mu-Chu Lee, Chih-Jen Lin:
Parallel Dual Coordinate Descent Method for Large-scale Linear Classification in Multi-core Environments. 1485-1494 - Edward Choi, Mohammad Taha Bahadori, Elizabeth Searles, Catherine Coffey, Michael Thompson, James Bost, Javier Tejedor-Sojo, Jimeng Sun:
Multi-layer Representation Learning for Medical Concepts. 1495-1504 - Lingyang Chu, Zhefeng Wang, Jian Pei, Jiannan Wang, Zijin Zhao, Enhong Chen:
Finding Gangs in War from Signed Networks. 1505-1514 - Mustafa Coskun, Ananth Grama, Mehmet Koyutürk:
Efficient Processing of Network Proximity Queries via Chebyshev Acceleration. 1515-1524 - Dingxiong Deng, Cyrus Shahabi, Ugur Demiryurek, Linhong Zhu, Rose Yu, Yan Liu:
Latent Space Model for Road Networks to Predict Time-Varying Traffic. 1525-1534 - Laxman Dhulipala, Igor Kabiljo, Brian Karrer, Giuseppe Ottaviano, Sergey Pupyrev, Alon Shalita:
Compressing Graphs and Indexes with Recursive Graph Bisection. 1535-1544 - Denis Moreira dos Reis, Peter A. Flach, Stan Matwin, Gustavo E. A. P. A. Batista:
Fast Unsupervised Online Drift Detection Using Incremental Kolmogorov-Smirnov Test. 1545-1554 - Nan Du, Hanjun Dai, Rakshit Trivedi, Utkarsh Upadhyay, Manuel Gomez-Rodriguez, Le Song:
Recurrent Marked Temporal Point Processes: Embedding Event History to Vector. 1555-1564 - Geli Fei, Shuai Wang, Bing Liu:
Learning Cumulatively to Become More Knowledgeable. 1565-1574 - Yihan Gao, Aditya G. Parameswaran:
Squish: Near-Optimal Compression for Archival of Relational Datasets. 1575-1584 - Lei Han, Yu Zhang, Tong Zhang:
Fast Component Pursuit for Large-Scale Inverse Covariance Estimation. 1585-1594 - Zhipeng Huang, Yudian Zheng, Reynold Cheng, Yizhou Sun, Nikos Mamoulis, Xiang Li:
Meta Structure: Computing Relevance in Large Heterogeneous Information Networks. 1595-1604 - Zhouyuan Huo, Feiping Nie, Heng Huang:
Robust and Effective Metric Learning Using Capped Trace Norm: Metric Learning via Capped Trace Norm. 1605-1614 - Bo Kang, Jefrey Lijffijt, Raúl Santos-Rodriguez, Tijl De Bie:
Subjectively Interesting Component Analysis: Data Projections that Contrast with Prior Expectations. 1615-1624 - Purushottam Kar, Shuai Li, Harikrishna Narasimhan, Sanjay Chawla, Fabrizio Sebastiani:
Online Optimization Methods for the Quantification Problem. 1625-1634 - Mohammad Reza Karimi, Erfan Tavakoli, Mehrdad Farajtabar, Le Song, Manuel Gomez-Rodriguez:
Smart Broadcasting: Do You Want to be Seen? 1635-1644 - Joon Hee Kim, Amin Mantrach, Alejandro Jaimes, Alice Oh:
How to Compete Online for News Audience: Modeling Words that Attract Clicks. 1645-1654 - Erich Kummerfeld, Joseph D. Ramsey:
Causal Clustering for 1-Factor Measurement Models. 1655-1664 - Igor Labutov, Frans Schalekamp, Kelvin Luu, Hod Lipson, Christoph Studer:
Optimally Discriminative Choice Sets in Discrete Choice Models: Application to Data-Driven Test Design. 1665-1674 - Himabindu Lakkaraju, Stephen H. Bach, Jure Leskovec:
Interpretable Decision Sets: A Joint Framework for Description and Prediction. 1675-1684 - Arnon Lazerson, Daniel Keren, Assaf Schuster:
Lightweight Monitoring of Distributed Streams. 1685-1694 - Benjamin Letham, Lydia M. Letham, Cynthia Rudin:
Bayesian Inference of Arrival Rate and Substitution Behavior from Sales Transaction Data with Stockouts. 1695-1704 - Qingyang Li, Shuang Qiu, Shuiwang Ji, Paul M. Thompson, Jieping Ye, Jie Wang:
Parallel Lasso Screening for Big Data Optimization. 1705-1714 - Yan Li, Jie Wang, Jieping Ye, Chandan K. Reddy:
A Multi-Task Learning Formulation for Survival Analysis. 1715-1724 - Yanni Li, Hui Li, Tihua Duan, Sheng Wang, Zhi Wang, Yang Cheng:
A Real Linear and Parallel Multiple Longest Common Subsequences (MLCS) Algorithm. 1725-1734 - Kaixiang Lin, Jianpeng Xu, Inci M. Baytas, Shuiwang Ji, Jiayu Zhou:
Multi-Task Feature Interaction Learning. 1735-1744 - Hongfu Liu, Ming Shao, Sheng Li, Yun Fu:
Infinite Ensemble for Image Clustering. 1745-1754 - Antonio Maccioni, Daniel J. Abadi:
Scalable Pattern Matching over Compressed Graphs via Dedensification. 1755-1764 - Ahmad Mahmoody, Charalampos E. Tsourakakis, Eli Upfal:
Scalable Betweenness Centrality Maximization via Sampling. 1765-1773 - Xin Mu, Feida Zhu, Ee-Peng Lim, Jing Xiao, Jianzong Wang, Zhi-Hua Zhou:
User Identity Linkage by Latent User Space Modelling. 1775-1784 - Kazuya Nakagawa, Shinya Suzumura, Masayuki Karasuyama, Koji Tsuda, Ichiro Takeuchi:
Safe Pattern Pruning: An Efficient Approach for Predictive Pattern Mining. 1785-1794 - Zhi Nie, Pinghua Gong, Jieping Ye:
Predict Risk of Relapse for Patients with Multiple Stages of Treatment of Depression. 1795-1804 - Adi Omari, Benny Kimelfeld, Eran Yahav, Sharon Shoham:
Lossless Separation of Web Pages into Layout Code and Data. 1805-1814 - Siddharth Reddy, Igor Labutov, Siddhartha Banerjee, Thorsten Joachims:
Unbounded Human Learning: Optimal Scheduling for Spaced Repetition. 1815-1824 - Xiang Ren, Wenqi He, Meng Qu, Clare R. Voss, Heng Ji, Jiawei Han:
Label Noise Reduction in Entity Typing by Heterogeneous Partial-Label Embedding. 1825-1834 - Polina Rozenshtein, Aristides Gionis, B. Aditya Prakash, Jilles Vreeken:
Reconstructing an Epidemic Over Time. 1835-1844 - Tianlin Shi, Forest Agostinelli, Matthew Staib, David P. Wipf, Thomas Moscibroda:
Improving Survey Aggregation with Sparsely Represented Signals. 1845-1854 - Yu Shi, Myunghwan Kim, Shaunak Chatterjee, Mitul Tiwari, Souvik Ghosh, Rómer Rosales:
Dynamics of Large Multi-View Social Networks: Synergy, Cannibalization and Cross-View Interplay. 1855-1864 - Leilei Sun, Chuanren Liu, Chonghui Guo, Hui Xiong, Yanming Xie:
Data-driven Automatic Treatment Regimen Development and Recommendation. 1865-1874 - Yasuo Tabei, Hiroto Saigo, Yoshihiro Yamanishi, Simon J. Puglisi:
Scalable Partial Least Squares Regression on Grammar-Compressed Data Matrices. 1875-1884 - Mengting Wan, Xiangyu Chen, Lance M. Kaplan, Jiawei Han, Jing Gao, Bo Zhao:
From Truth Discovery to Trustworthy Opinion Discovery: An Uncertainty-Aware Quantitative Modeling Approach. 1885-1894 - Beidou Wang, Martin Ester, Yikang Liao, Jiajun Bu, Yu Zhu, Ziyu Guan, Deng Cai:
The Million Domain Challenge: Broadcast Email Prioritization by Cross-domain Recommendation. 1895-1904 - Ying Wei, Yu Zheng, Qiang Yang:
Transfer Knowledge between Cities. 1905-1914 - Hao Wu, Jiangyun Mao, Weiwei Sun, Baihua Zheng, Hanyuan Zhang, Ziyang Chen, Wei Wang:
Probabilistic Robust Route Recovery with Spatio-Temporal Dynamics. 1915-1924 - Houping Xiao, Jing Gao, Zhaoran Wang, Shiyu Wang, Lu Su, Han Liu:
A Truth Discovery Approach with Theoretical Guarantee. 1925-1934 - Houping Xiao, Jing Gao, Qi Li, Fenglong Ma, Lu Su, Yunlong Feng, Aidong Zhang:
Towards Confidence in the Truth: A Bootstrapping based Truth Discovery Approach. 1935-1944 - Haichuan Yang, Ryohei Fujimaki, Yukitaka Kusumura, Ji Liu:
Online Feature Selection: A Limited-Memory Substitution Algorithm and Its Asynchronous Parallel Variation. 1945-1954 - Tao Yang, Jun Liu, Pinghua Gong, Ruiwen Zhang, Xiaotong Shen, Jieping Ye:
Absolute Fused Lasso and Its Application to Genome-Wide Association Studies. 1955-1964 - Yi Yang, Da Yan, Huanhuan Wu, James Cheng, Shuigeng Zhou, John C. S. Lui:
Diversified Temporal Subgraph Pattern Mining. 1965-1974 - Yuan Yang, Jianfei Chen, Jun Zhu:
Distributing the Stochastic Gradient Sampler for Large-Scale LDA. 1975-1984 - Wei Ye, Sebastian Goebl, Claudia Plant, Christian Böhm:
FUSE: Full Spectral Clustering. 1985-1994 - Jianhua Yin, Jianyong Wang:
A Text Clustering Algorithm Using an Online Clustering Scheme for Initialization. 1995-2004 - Ganzhao Yuan, Yin Yang, Zhenjie Zhang, Zhifeng Hao:
Convex Optimization for Linear Query Processing under Approximate Differential Privacy. 2005-2014 - Chengxi Zang, Peng Cui, Christos Faloutsos:
Beyond Sigmoids: The NetTide Model for Social Network Growth, and Its Applications. 2015-2024 - Chunqiu Zeng, Qing Wang, Shekoofeh Mokhtari, Tao Li:
Online Context-Aware Recommendation with Time Varying Multi-Armed Bandit. 2025-2034 - Aston Zhang, Quanquan Gu:
Accelerated Stochastic Block Coordinate Descent with Optimal Sampling. 2035-2044 - Lei Zhang, Shupeng Wang, Xiaoyu Zhang, Yong Wang, Binbin Li, Dinggang Shen, Shuiwang Ji:
Collaborative Multi-View Denoising. 2045-2054 - Xiaoxuan Zhang, Tianbao Yang, Padmini Srinivasan:
Online Asymmetric Active Learning with Imbalanced Data. 2055-2064 - Yuyu Zhang, Mohammad Taha Bahadori, Hang Su, Jimeng Sun:
FLASH: Fast Bayesian Optimization for Data Analytic Pipelines. 2065-2074 - Hongke Zhao, Qi Liu, Guifeng Wang, Yong Ge, Enhong Chen:
Portfolio Selections in P2P Lending: A Multi-Objective Perspective. 2075-2084 - Liang Zhao, Jieping Ye, Feng Chen, Chang-Tien Lu, Naren Ramakrishnan:
Hierarchical Incomplete Multi-source Feature Learning for Spatiotemporal Event Forecasting. 2085-2094 - Guoqing Zheng, Yiming Yang, Jaime G. Carbonell:
Efficient Shift-Invariant Dictionary Learning. 2095-2104 - Yuan Zuo, Junjie Wu, Hui Zhang, Hao Lin, Fei Wang, Ke Xu, Hui Xiong:
Topic Modeling of Short Texts: A Pseudo-Document View. 2105-2114
Tutorials
- John Mark Agosta, Debraj GuhaThakurta, Robert Horton, Mario Inchiosa, Srini Kumar, Mengyue Zhao:
Scalable Data Analytics Using R: Single Machines to Hadoop Spark Clusters. 2115 - Zhiyuan Chen, Estevam R. Hruschka Jr., Bing Liu:
Lifelong Machine Learning and Computer Reading the Web. 2117-2118 - Gianmarco De Francisci Morales, Albert Bifet, Latifur Khan, João Gama, Wei Fan:
IoT Big Data Stream Mining. 2119-2120 - Jing Gao, Qi Li, Bo Zhao, Wei Fan, Jiawei Han:
Mining Reliable Information from Passively and Actively Crowdsourced Data. 2121-2122 - Ashish Gupta, Neera Agarwal:
Streaming Analytics. 2123 - Sara Hajian, Francesco Bonchi, Carlos Castillo:
Algorithmic Bias: From Discrimination Discovery to Fairness-aware Data Mining. 2125-2126 - Yuheng Hu, Yu-Ru Lin, Jiebo Luo:
Collective Sensemaking via Social Sensors: Extracting, Profiling, Analyzing, and Predicting Real-world Events. 2127-2128 - Abdullah Mueen, Eamonn J. Keogh:
Extracting Optimal Performance from Dynamic Time Warping. 2129-2130 - François Petitjean, Geoffrey I. Webb:
Scalable Learning of Graphical Models. 2131-2132 - B. Aditya Prakash, Naren Ramakrishnan:
Leveraging Propagation for Data Mining: Models, Algorithms and Applications. 2133-2134 - Frank Seide, Amit Agarwal:
CNTK: Microsoft's Open-Source Deep-Learning Toolkit. 2135 - Fei Wang, Ping Zhang, Joel Dudley:
Healthcare Data Mining with Matrix Models. 2137-2138 - Qiang Zhu, Songtao Guo, Paul Ogilvie, Yan Liu:
Business Applications of Predictive Modeling at Scale. 2139-2140
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