MONDAY- Aug 12th |
Chairs |
Rooms |
|
10:30-12pm |
1: Document and topic models |
David Gleich |
Chicago 8 |
|
2: Social media |
Jure Leskovec |
Chicago 9 |
|
3: Big data frameworks |
Wei Wang |
Chicago 10 |
3-4:30pm |
4: Graph mining |
Ian Davidson |
Chicago 8 |
|
5: Classification |
Chih-Jen Lin |
Chicago 9 |
5-6:10pm |
6: Healthcare and bioinformatics |
Jimeng Sun |
Chicago 8 |
|
7: Recommender systems |
Thorsten Joachims |
Chicago 9 |
TUESDAY- Aug 13th |
|
10:30-12pm |
8: Temporal/social influence |
Jie Tang |
Chicago 8 |
|
9: Sparse learning |
Jieping Ye |
Chicago 9 |
|
10: Graph clustering |
Neel Sundaresan |
Chicago 10 |
3-4:30pm |
11: Scalable methods for big data |
Tina Eliassi-Rad |
Chicago 8 |
|
12: Diffusion in social networks |
Chris Clifton |
Chicago 9 |
|
13: Time series and spatial data |
Tanya Berger-Wolf |
Chicago 10 |
5-6:30pm |
14: Unsupervised and topic learning |
Jiawei Han |
Chicago 8 |
|
15: Social and information networks |
Shou-De Lin |
Chicago 9 |
WEDNESDAY- Aug 14th |
|
||
10:30-12pm |
16: Graph mining and sampling |
Hanghang Tong |
Chicago 8 |
|
17: Rule and pattern mining |
Francesco Bonchi |
Chicago 9 |
|
18: Web mining |
Ronny Kohavi |
Chicago 10 |
|
Best Papers [Joint Research and IG] |
|
Chicago 6/7 |
PRESENTERS PLEASE NOTE: All research talks & best papers are no more than 20 minutes. This includes time for questions.
Monday 10:30-12pm (90 min session)
Research Session 1: Document and topic models
• 980 One Theme in All Views: Modeling Consensus Topics in Multiple Contexts
Authors: Jian Tang, Peking University; Ming Zhang, ; Qiaozhu Mei, University of Michigan
• 198 Representing Documents Through Their Readers
Authors: Khalid El-Arini, Carnegie Mellon University; Min Xu, Carnegie Mellon University; Emily Fox, University of Washington; Carlos Guestrin, University of Washington
• 811 Text-Based Measures of Document Diversity
Authors: Kevin Bache, University of California, Irvine; Padhraic Smyth, UC Irvine; David Newman, University of California, Irvine
• 528 Diversity Maximization Under Matroid Constraints
Authors: Zeinab Abbassi, Columbia University; Vahab Mirrokni, Google; Mayur Thakur, Google
Research Session 2: Social media
• 611 Connecting Users across Social Media Sites: A Behavioral-Modeling Approach
Authors: Reza Zafarani, Arizona State University; Huan Liu, Arizona State University
• 722 Automatic selection of social media responses to news
Authors: Tadej _tajner, Jo_ef Stefan Institute; Bart Thomee, Yahoo! Research; Ana Maria Popescu, Yahoo! Labs; Marco Pennacchiotti, eBay Inc.; Alejandro Jaimes, Yahoo!
• 1041 Estimating Unbiased Sharer Reputation via Social Data Calibration
Authors: Jaewon Yang, Stanford University; Bee-Chung Chen, LinkedIn; Deepak Agarwal, LinkedIn
• 1045 Linking Named Entities in Tweets with Knowledge Base via User Interest Modeling
Authors: Wei Shen, Tsinghua University; Jianyong Wang, Tsinghua University; Ping Luo, HP Lab; Min Wang, Google Research
Research Session 3: Big data frameworks
• 52 TurboGraph: A Fast Parallel Graph Engine Handling Billion-scale Graphs in a Single PC
Authors: Wook-Shin Han, POSTECH; Sangyeon Lee, POSTECH; Kyungyeol Park, POSTECH; Jeong-Hoon Lee, POSTECH; Min-Soo Kim, DGIST; Jinha Kim, POSTECH; Hwanjo Yu, POSTECH
• 142 A Probabilistic Framework for Big Data Pipelines
Authors: Karthik Raman, Cornell University; Adith Swaminathan, Cornell University; Thorsten Joachims, Cornell; Johannes Gehrke, Cornell University
• 914 Big Data Analytics with Small Footprint: Squaring the Cloud
Authors: John Canny, UC Berkeley; Huasha Zhao, UC Berkeley
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Monday 3:00-4:30pm (90 min session)
Research Session 4: Graph mining
• 583 Denser than the densest subgraph: extracting optimal quasi-cliques with quality guarantees
Authors: Charalampos Tsourakakis, Carnegie Mellon University; Francesco Bonchi, Yahoo! Research; Aristides Gionis, Aalto University; Francesco Gullo, Yahoo! Research; Maria Tsiarli, University of Pittsburgh
• 399 Guided Learning for Role Discovery (GLRD): Framework, Algorithms, and Applications
Authors: Sean Gilpin, U.C. Davis; Tina Eliassi-Rad, ; Ian Davidson, University of California – Davis
• 1083 Redundancy-Aware Maximal Cliques
Authors: Jia Wang, Chinese University of Hong Kong; James Cheng, Chinese University of Hong Kong; Ada Wai-Chee Fu, Chinese University of Hong Kong
• 569 Selective Sampling on Graphs for Classification
Authors: Quanquan Gu, CS, UIUC; Charu Aggarwal, IBM Research; Jialu Liu, UIUC; Jiawei Han, University of Illinois at Urbana-Champaign
Research Session 5: Classification
• 95 Density-Based Logistic Regression
Authors: Wenlin Chen, Yixin Chen, Washington University in St Louis; Yi Mao, Baolong Guo, Xidian University
• 627 MILS: Multi-Instance Learning from Multiple Information Sources
Authors: Dan Zhang, Purdue University; Jingrui He, Stevens Institute of Technolog; Richard Lawrence, IBM Research
• 572 Querying Discriminative and Representative Samples for Batch Mode Active Learning
Authors: Zheng Wang, Arizona State University; Jieping Ye, Arizona State University
• 863 SVM_{pAUC}^{tight}: A New Support Vector Method for Optimizing Partial AUC Based on a Tight Convex Upper Bound
Authors: Harikrishna Narasimhan, Indian Institute of Science; Shivani Agarwal, Indian Institute of Science, Bangalore
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Monday 5:00-6:10pm (70 min session)
Research Session 6:Healthcare and bioinformatics
• 543 Succinct Interval-Splitting Tree for Scalable Similarity Search of Compound-Protein Pairs with Property Constraints
Authors: Yasuo Tabei, JST; Akihiro Kishimoto, IBM Research, Dublin; Masaaki Kotera, Kyoto University; Yoshihiro Yamanishi, Kyushu university
• 191 Multi-Source Learning with Block-wise Missing Data For Alzheimer’s Disease Prediction
Authors: Shuo Xiang, Arizona State University; Lei Yuan, Arizona State University; Wei Fan, IBM Research; Yalin Wang, ; Paul Thompson, ; Jieping Ye, Arizona State University
• 395 Network Discovery via Constrained Tensor Analysis of fMRI Data
Authors: Ian Davidson, University of California – Davis
Research Session 7: Recommender systems
• 631 Learning to question: Leveraging user preferences for shopping advice
Authors: Mahashweta Das, Univ of Texas at Arlington; Gianmarco De Francisci Morales, Yahoo! Research; Aristides Gionis, Aalto University; Ingmar Weber, Qatar Computing Research Institute
• 444 Active Learning and Search on Low-Rank Matrices
Authors: Dougal Sutherland, Carnegie Mellon University; Barnab‡s P—czos, Carnegie Mellon University; Jeff Schneider,
• 293 LCARS: A Location-Content-Aware Recommender System
Authors: Hongzhi Yin, Peking University; Yizhou Sun, ; Bin Cui, Peking University; Zhiting Hu, ; Ling Chen
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Tuesday 10:30-12pm (90 min session)
Research Session 8: Temporal/social influence
• 425 Discovering Latent Influence in Online Social Activities via Shared Cascade Poisson Processes
Authors: Tomoharu Iwata, NTT Communication Science Laboratories; Amar Shah, University of Cambridge; Zoubin Ghahramani, Cambridge University
• 707 STRIP: Stream Learning of Influence Probabilities
Authors: Konstantin Kutzkov, University of Copenhagen; Albert Bifet, Yahoo! Research; Francesco Bonchi, Yahoo! Research; Aristides Gionis, Aalto University
• 18 Fast Structure Learning in Generalized Stochastic Processes with Latent Factors
Authors: Mohammad Taha Bahadori, University of Southern Califor; Yan Liu, University of Southern California; Eric Xing, CMU
Research Session 9: Sparse learning
• 770 Robust Sparse Estimation of Multiresponse Regression and Inverse Covariance Matrix via the L2 distance
Authors: Aurelie Lozano, IBM Research; Huijing Jiang, IBM Research; Xinwei Deng, Virginia Tech
• 1167 Exact Sparse Recovery with L0 Projections
Authors: Ping Li, Cornell University; Cun-Hui Zhang, Rutgers University
• 251 Robust Principal Component Analysis via Capped Norms
Authors: Qian Sun, Arizona State University; Shuo Xiang, Arizona State University; Jieping Ye, Arizona State University
Research Session 10: Graph clustering
• 93 Flexible and Robust Co-regularized Multi-Domain Graph Clustering
Authors: Wei Cheng, UNC at Chapel Hill; xiang Zhang, Case Western Reserve University; Patrick Sullivan, UNC at Chapel Hill; Wei Wang, University of California, Los Angeles
• 1186 Clustered Graph Randomization: Network Exposure to Multiple Universes
Authors: Johan Ugander, Cornell University; Brian Karrer, Facebook; Lars Backstrom, Facebook; Jon Kleinberg, Cornell
• 566 Social Influence Based Clustering of Heterogeneous Information Networks
Authors: Yang Zhou, Georgia Institute of Technolog; Ling Liu, Georgia Institute of Technology
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Tuesday 3-4:30pm (90 min session)
Research Session 11: Scalable methods for big data
• 773 Comparing Apples to Oranges: A Scalable Solution with Heterogeneous Hashing
Authors: Mingdong Ou, Tsinghua University; Peng Cui, Tsinghua University; Fei Wang, IBM T. J. Watson Research Lab; Jun Wang, IBM Research
• 166 Fast and Scalable Polynomial Kernels via Explicit Feature Maps
Authors: Ninh Pham, IT University of Copenhagen; Rasmus Pagh, IT University of Copenhagen
• 434 Indexed Block Coordinate Descent for Large-Scale Linear Classification with Limited Memory
Authors: En-Hsu Yen, National Taiwan University; Chun-Fu Chang, National Taiwan University; Ting-Wei Lin, National Taiwan University; Shan-Wei Lin, National Taiwan University; Shou-De Lin, National Taiwan University
• 577 Recursive Regularization for Large-scale Classification with Hierarchical and Graphical Dependencies
Authors: Siddharth Gopal, CMU; Yiming Yang, CMU
Research Session 12: Diffusion in social networks
• 1163 Confluence: Conformity Influence in Large Social Networks
Authors: Jie Tang, Tsinghua University; Sen Wu, Tsinghua University; Jimeng Sun, IBM Research
• 291 The Role of Information Diffusion in the Evolution of Social Networks
Authors: Lilian Weng, Indiana University; Jacob Ratkiewicz, Google Inc.; Nicola Perra, Northeastern University; Bruno Goncalves, Aix-Marseille Universite; Carlos Castillo, Qatar Computing Research Institute; Francesco Bonchi, Yahoo! Research; Rossano Schifanella, Universita degli Studi di Torino, Italy; Filippo Menczer, Indiana University; Alessandro Flammini, Indiana University
• 1006 Information Cascade at Group Scale
Authors: Milad Eftekhar, University of Toronto; Yashar Ganjali, University of Toronto; Nick Koudas, University of Toronto
• 120 Extracting Social Events for Learning Better Information Diffusion Models
Authors: Shuyang Lin, UIC; Fengjiao Wang, University of Illinois at Chic; Qingbo Hu, University of Illinois at Chic; philip Yu, University of Illinois at Chicago
Research Session 13: Time series and spatial data
• 341 Model Selection in Markovian Procsses
Authors: Assaf Hallak, The Technion; Dotan Di-Castro, Technion; Shie Mannor, Technion
• 511 DTW-D: Time Series Semi-Supervised Learning from a Single Example
Authors: Yanping Chen, UCR; Bing Hu, ; Eamonn Keogh, University of California – Riverside; Gustavo Batista,
• 1287 Model-based Kernel for Efficient Time Series Analysis
Authors: Huanhuan Chen, University of Birmingham; Fengzhen Tang, University of Birmingham; Peter Tino, University of Birmingham; Xin Yao, University of Birmingham
• 131 Mining Lines in the Sand: On Trajectory Discovery From Untrustworthy Data in Cyber-Physical System
Authors: Lu-An Tang, UIUC; Xiao Yu, University of Illinois at Urbana-Champaign; Quanquan Gu, CS, UIUC; Jiawei Han, UIUC; Alice Leung, BBN; Thomas La Porta, PSU
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Tuesday 5-6:30pm (90 min session)
Research Session 14: Unsupervised and topic learning
• 623 A General Bootstrap Performance Diagnostic
Authors: Ariel Kleiner, ; Ameet Talwalkar, UC Berkeley; Sameer Agarwal, ; Michael Jordan, ; Ion Stoica,
• 897 Subsampling for Efficient and Effective Unsupervised Outlier Detection Ensembles
Authors: Arthur Zimek, University of Alberta; Matthew Gaudet, University of Alberta; Ricardo J. G. Campello, University of Alberta; Jšrg Sander, University of Alberta
• 503 A Phrase Mining Framework for Recursive Construction of a Topical Hierarchy
Authors: Chi Wang, University of Illinois; Marina Danilevsky, University of Illinois; Nihit Desai, University of Illinois at Urbana-Champaign; Yinan Zhang, University of Illinois at Urbana-Champaign; Phuong Nguyen, University of Illinois at Urbana-Champaign; Thrivikrama Taula, University of Illinois at Urbana-Champaign; Jiawei Han, University of Illinois at Urbana-Champaign
• 1199 Stochastic Collapsed Variational Bayesian Inference for Latent Dirichlet Allocation
Authors: James Foulds, UC Irvine; Levi Boyles, UC Irvine; Christopher Dubois, UC Irvine; Padhraic Smyth, UC Irvine; max Welling, University of Amsterdam
Research Session 15: Social and information networks
• 571 WiseMarket: A New Paradigm for Managing Wisdom of Online Social Users
Authors: Chen Cao, HKUST; Yongxin Tong, HKUST; Lei Chen, HKUST; H.V. Jagadish, University of Michigan
• 295 Multi-Label Relational Neighbor Classification using Social Context Features
Authors: Xi Wang, University of Central Florida; Gita Sukthankar, University of Central Florida
• 1162 Scalable Text and Link Analysis with Mixed-Topic Link Models
Authors: YAOJIA ZHU, University of New Mexico; Xiaoran Yan, University of New Mexico; Lise Getoor, The University of Maryland College Park; Cristopher Moore, Santa Fe Institute
• 730 Collaborative Boosting for Activity Classification in Microblogs
Authors: Yangqiu Song, HKUST; Zhengdong Lu, Huawei; Cane Wing-Ki Leung, Huawei; Qiang Yang, Hong Kong University of Science and Technology
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Wednesday 10:30-12pm (90 min session)
Research Session 16: Graph mining and sampling
• 752 Trace Complexity of Network Inference
Authors: Bruno Abrahao, Cornell; Flavio Chierichetti, Sapienza University; Robert Kleinberg, Cornell; Alessandro Panconesi, Sapienza University of Rome
• 1024 Debiasing Social Wisdom
Authors: Abhimanyu Das, Microsoft; Sreenivas Gollapudi, Microsoft Research; Rina Panigrahy, Microsoft Research; Mahyar Salek, Microsoft
• 1148 Mining Discriminative Subgraphs from Global-state Networks
Authors: Sayan Ranu, IBM; Minh Hoang, UC Santa Barbara; Ambuj Singh, UC Santa Barbara
• 249 Approximate Graph Mining with Label Costs
Authors: Pranay Anchuri, RPI; Mohammed Zaki, Rensselaer Polytechnic Institute; Omer Barkol, HP Labs; Shahar Golan, HP Labs; Moshe Shamy, HP Labs
Research Session 17: Rule and pattern mining
• 392 Summarizing Probabilistic Frequent Patterns: A Fast Approach
Authors: Chunyang Liu, UTS; Ling Chen, ; Chengqi Zhang, QCIS, University of Technology, Sydney
• 668 Mining High Utility Episodes in Complex Event Sequences
Authors: Cheng-Wei Wu, National Cheng Kung University; Yu Feng Lin, National Cheng Kung University, Taiwan, ROC; Philip Yu, University of Illinois; Vincent Tseng, National Cheng Kung University
• 245 Mining Frequent Graph Patterns with Differential Privacy
Authors: Entong Shen, North Carolina State Univ; Ting Yu, North Carolina State University
Research Session 18: Web mining
• 240 Statistical Quality Estimation for General Crowdsourcing Tasks
Authors: Yukino Baba, The University of Tokyo; Hisashi Kashima, The University of Tokyo
• 1205 Exploring Consumer Psychology for Click Prediction in Sponsored Search
Authors: Taifeng Wang, Microsoft; Jiang Bian, ; Tie-Yan Liu, Microsoft Research
• 172 SiGMa: Simple Greedy Matching for Aligning Large Knowledge Bases
Authors: Simon Lacoste-Julien, INRIA / ENS; Konstantina Palla, University of Cambridge; Alex Davies, University of Cambridge; Gjergji Kasneci, Microsoft Research; Thore Graepel, Microsoft Research; Zoubin Ghahramani, Cambridge University
Monday 6:30-8:30pm
Research Poster Session