KDD 2010 accepted papers

www.kdd.org/kdd2010/papers.shtml.

Research Full Presentations

• A Hierarchical Information Theoretic Technique for the Discovery of Non Linear Alternative Clusterings
  Xuan Hong Dang*, The University of Melbourne; James Bailey, The University of Melbourne
• A Scalable Two-Stage Approach for a Class of Dimensionality Reduction Techniques
  Liang Sun*, Arizona State University; Betul Ceran, Arizona State University; Jieping Ye, Arizona State University
• A Statistical Model for Popular Event Tracking in Social Communities
  Xide Lin*, UIUC; Bo Zhao, U of Illinois,Urbana Champaign; Qiaozhu Mei, Univ. of Michigan; Jiawei Han,
• An Efficient Algorithm for a Class of Fused Lasso Problems
  Jun Liu*, ASU; Lei Yuan, ; Jieping Ye, Arizona State University
• An efficient causal discovery algorithm for linear models
  Zhenxing Wang*, The Chinese University of Hong; Laiwan Chan, The Chinese University of Hong Kong
• An Energy-Efficient Mobile Recommender System
  Yong Ge*, Rutgers University; Hui Xiong, Rutgers University; Alexander Tuzhilin, Stern School of Business, New York University; Keli Xiao, Rutgers University; Marco Gruteser, Rutgers University
• Balanced Allocation with Succinct Representation
  Saeed Alaei, University of Maryland; Ravi Kumar*, Yahoo; Azaraksh Malekian, UMD; Erik Vee, Yahoo! Research
• Class-Specific Error Bounds for Ensemble Classifiers
  Ryan Prenger*, Lawrence Livermore National La; Tracy Lemmond, Lawrence Livermore National Laboratory; Barry Chen, Lawrence Livermore National Laboratory; Kush Varshney, Massachusetts Institute of Technology; William Hanley, Lawrence Livermore National Laboratory
• Clustering by Synchronization
  Christian Böhm*, University of Munich; Claudia Plant, Technische Universität München; Junming Shao, University of Munich; Qinli Yang, University of Edinburgh
• Collusion-Resistant Privacy-Preserving Data Mining
  Bin Yang*, The University of Tokyo; Hiroshi Nakagawa, ; issei Sato, ; Jun Sakuma, University of Tsukuba
• Combined Regression and Ranking
  D. Sculley*, Google, Inc
• Combining Predictions for Accurate Recommender Systems
  Michael Jahrer*, Commendo research & consulting; Andreas Töscher, Commendo research & consulting; Robert Legenstein, Graz University of Technology
• Community Outliers and their Efficient Detection in Information Networks
  Jing Gao*, UIUC; Feng Liang, UIUC; Wei Fan, IBM T.J.Watson; Chi Wang, UIUC; Yizhou Sun, University of Illinois at Urbana Champaign; Jiawei Han, UIUC
• Compressed Fisher Linear Discriminant Analysis: Classification of Randomly Projected Data
  Robert Durrant*, University of Birmingham; Ata Kaban, University of Birmingham
• Connecting the Dots Between News Articles
  Dafna Shahaf*, CMU; Carlos Guestrin, CMU
• Data Mining with Differential Privacy
  Arik Friedman*, Technion; Assaf Schuster, Technion
• Designing efficient cascaded classifiers: Tradeoff between accuracy and cost
  Vikas Raykar*, Siemens Healthcare; Balaji Krishnapuram, Siemens Healthcare; Shipeng Yu, Siemens Healthcare
• Discovering frequent patterns in sensitive data
  Raghav Bhaskar, Microsoft Research; Srivatsan Laxman*, Microsoft Research; Adam Smith, Pennsylvania State University; Abhradeep Thakurta, Pennsylvania State University
• Discovering Significant Relaxed Order-Preserving Submatrices
  Qiong FANG*, HKUST; Wilfred Ng, Hong Kong UST; Jianlin Feng, Sun Yat-sen University
• Discriminative Topic Modeling based on Manifold Learning
  Seungil Huh*, Carnegie Mellon University; Stephen Fienberg,
• Document Clustering via Dirichlet Process Mixture Model with Feature Selection
  Guan Yu, ; Ruizhang Huang*, The Hong Kong Polytechnic Univ; Zhaojun Wang,
• DUST: A Generalized Notion of Similarity between Uncertain Time Series
  Smruti Sarangi, IBM Research, India; Karin Murthy*, IBM Research, India
• Estimating Rates of Rare Events with Multiple Hierarchies through Scalable Log-linear Models
  Deepak Agarwal*, ; Nagaraj Kota, ; Rahul Agrawal, ; Rajiv Khanna,
• Evolutionary Hierarchical Dirichlet Processes for Multiple Correlated Time-varying Corpora
  Jianwen Zhang*, Tsinghua University; Yangqiu Song, ; Changshui Zhang, Tsinghua University; Shixia Liu,
• Extracting Temporal Signatures for Comprehending Systems Biology Models
  Naren Sundaravaradan, Virginia Tech; K. S. M. Tozammel Hossain, Virginia Tech; Vandana Sreedharan, Virginia Tech; John Paul Vergara, Ateneo de Manila University; Lenwood Heath, Virginia Tech; Douglas Slotta, NIH/NCBI; Naren Ramakrishnan*, Virginia Tech
• Fast Euclidean Minimum Spanning Tree: Algorithm, Analysis, Applications
  William March*, Georgia Institute of Technolog; Parikshit Ram, Georgia Institute of Technology; Alexander Gray, Georgia Institute of Technology
• Fast Nearest Neighbor Search in Disk-resident Graphs
  Purnamrita Sarkar*, CMU; Andrew Moore, Google
• Fast Online Learning through Effective Offline Initialization for Time-Sensitive Recommendation
  Bee-Chung Chen*, Yahoo! Research; Deepak Agarwal, ; Pradheep Elango, Yahoo! Labs
• Fast Query Execution for Retrieval Models based on Path Constraint Random Walks
  Ni Lao*, Carnegie Mellon University; William Cohen, Carnegie Mellon University
• Flexible Constrained Spectral Clustering
  Xiang Wang*, UC Davis; Ian Davidson, UC Davis
• Frequent Regular Itemset Mining
  Salvatore Ruggieri*, Università di Pisa
• GLS-SOD: A Generalized Local Statistical Approach for Spatial Outlier Detection
  Feng Chen*, Virginia Tech; Chang-Tien Lu, Virginia Tech
• Grafting-Light: Fast, Incremental Feature Selection and Structure Learning of Markov Random Fields
  Jun Zhu*, Carnegie Mellon University; Ni Lao, Carnegie Mellon University; Eric Xing, Carnegie Mellon Univresity
• Growing a tree in the forest: constructing folksonomies by integrating structured metadata
  Anon Plangprasopchok*, Information Sciences Institute; Kristina Lerman, USC; Lise Getoor, University of Maryland, College Park
• Inferring Networks of Diffusion and Influence
  Manuel Gomez Rodriguez*, Stanford University; Jure Leskovec, Stanford University; Andreas Krause, California Institute of Technology
• k-Support Anonymity based on Pseudo Taxonomy for Outsourcing of Frequent Itemset Mining
  Chih-Hua Tai*, Ntu; Philip Yu, University of Illinois at Chicago; Ming-Syan Chen,
• Large Linear Classification When Data Cannot Fit In Memory
  Hsiang-Fu Yu*, National Taiwan University; Cho-Jui Hsieh , ; Kai-Wei Chang, ; Chih-Jen Lin, National Taiwan University
• Learning Incoherent Sparse and Low-Rank Patterns from Multiple Tasks
  Jianhui Chen*, Arizona State University; Ji Liu, Arizona State University; Jieping Ye, Arizona State University
• Learning to Combine Discriminative Classifiers
  Chi-Hoon Lee*, Yahoo! Labs
• Learning with Cost Intervals
  Xu-Ying Liu*, Nanjing University; Zhi-Hua Zhou, Nanjing University
• Mass Estimation and Its Applications
  Kai Ming Ting*, Monash University; Guang-Tong Zhou, Shandong University; Fei Tony LIU, Monash University; James Tan, Monash University
• Mining Advisor-Advisee Relationships from Research Publication Networks
  Chi Wang*, UIUC; Jiawei Han, ; Yuntao Jia, ; Jie Tang, Tsinghua; Duo Zhang, UIUC; Yintao Yu, UIUC; Jingyi Guo,
• Mining Positive and Negative Patterns for Relevance Feature Discovery
  Yuefeng Li*, Queensland University of Techn; Abdulmohsen Algarni, ; Ning Zhong, Maebashi Institute of Technology, Japan
• Mining Program Workflow from Interleaved Traces
  Jian-Guang LOU*, Microsoft Research Asia; Qiang FU, Microsoft Research Asia; Shengqi YANG, Beijing Univ. of Posts and Telecom; Jiang LI, Microsoft Research Asia; Bin WU, Beijing Univ. of Posts and Telecom
• Mining Top-K Frequent Items in a Data Stream with Flexible Sliding Windows
  Hoang Thanh Lam*, TU Eindhoven; Toon Calders, technische Universiteit Eindhoven
• Mining Uncertain Data with Probabilistic Guarantees
  Liwen Sun*, University of Hong Kong; Reynold Cheng, University of Hong Kong; David Cheung, University of Hong Kong; Jiefeng Cheng,
• Modeling Relational Events via Latent Classes
  Christopher DuBois*, UC Irvine; Padhraic Smyth,
• Multi-Label Learning by Exploiting Label Dependency
  Min-Ling Zhang*, Hohai University; Kun Zhang, MPI for Biological Cybernetics
• Multi-Task Learning for Boosting with Application to Web Search Ranking
  Olivier Chapelle*, Yahoo! Research; Srinivas Vadrevu, Yahoo! Labd; Kilian Weinberger, Washington University in St. Louis; Pannagadatta Shivaswamy, Columbia University; Ya Zhang, Shanghai Jiaotong University; Belle Tseng, Yahoo! Labs
• Negative correlations in collaboration: concepts and algorithms
  Jinyan Li*, Nanyang Technological University, Singapore; Qian Liu, NTU; Tao Zeng, NTU
• Neighbor Query Friendly Compression of Social Networks
  Hossein Maserrat*, Simon Fraser University; Jian Pei, SFU
• Nonnegative Shared Subspace Learning and Its Application to Social Media Retrieval
  Sunil Gupta*, Curtin University; Dinh Phung, Curtin University; Brett Adams, Curtin University; Truyen Tran, Curtin University; Svetha Venkatesh, Curtin University
• On the Quality of Inferring Interests From Social Neighbors
  Zhen Wen*, IBM T.J. Watson Research; Ching-Yung Lin, IBM T.J. Watson Research Center
• Online Discovery and Maintenance of Time Series Motifs
  Abdullah Mueen*, UC Riverside; Eamonn Keogh, UC Riverside
• Online Multiscale Dynamic Topic Models
  Tomoharu Iwata*, ; Takeshi Yamada, NTT; Yasushi Sakurai, NTT; Naonori Ueda, NTT
• Oracle Classification - Learning What Really Matters
  Ulf Johansson*, University of Boras; Cecilia Sönströd, ; Tuve Löfström,
• Privacy-Preserving Outsourcing Support Vector Machines with Random Transformation
  Ming-Syan Chen*, ; Keng-Pei Lin, National Taiwan University
• Redefining Class Definitions using Constraint-Based Clustering
  Dan Preston*, Tufts University; Carla Brodley, Tufts University; Roni Khardon, Tufts University; Damien Sulla-Menashe, Boston University; Mark Friedl, Boston University
• Scalable Influence Maximization for Prevalent Viral Marketing in Large-Scale Social Networks
  Wei Chen, ; Chi Wang, UIUC; Yajun Wang*,
• Scalable Similarity Search with Optimized Kernel Hashing
  Junfeng He*, Columbia University; Wei Liu, Columbia University; Shih-Fu Chang, Columbia University
• Semi-Supervised and Sparse Metric Learning Using Alternating Direction Optimization
  Wei Liu*, CUHK; Shiqian Ma, ; Dacheng Tao, Nanyang Technological University; Jianzhuang Liu,
• Semi-supervised Feature Selection for Graph Classification
  Xiangnan Kong, University of Illinois; Philip Yu*, University of Illinois at Chicago
• Suggesting Friends Using the Implicit Social Graph
  Maayan Roth*, Google; Assaf Ben-David, Google; David Deutscher, Google, Inc; Ilan Horn, Google, Inc; Aril Leichtberg, Google; Naty Leiser, Google; Ron Merom, Google; Yossi Mattias, Google, Inc
• The community-search problem and how to plan a successful cocktail party
  Mauro Sozio, Max-Planck-Institut fur Informatik; Aristides Gionis*, Yahoo! Research Barcelona
• The new Iris Data: Modular Data Generators
  Iris Adae*, Universitaet Konstanz; Michael Berthold, University of Konstanz
• The Topic-Perspective Model for Social Tagging Systems
  Caimei Lu*, Drexel University; Xiaohua Hu, Drexel University; Xin Chen, Drexel University; Jung-ran Park, Drexel University
• Topic Dynamics: an alternative model of `Bursts' in Streams of Topics
  Dan He*, UCLA; Douglass Parker, UCLA Computer Science Dept
• Topic Models with Power-Law Using Pitman-Yor Process
  Issei Sato*, University of Tokyo; Hiroshi Nakagawa, University of Tokyo
• Training and Testing of Recommender Systems on Data Missing Not at Random
  Harald Steck*, Bell Labs, Alcatel-Lucent
• Trust Network Inference for Online Rating Data Using Generative Models
  Freddy Chong Tat Chua*, Singapore Management Universit; Ee-Peng Lim, Singapore Management University
• Unifying Dependent Clustering and Disparate Clustering for Non-homogeneous Data
  M. Shahriar Hossain, Virginia Tech; Satish Tadepalli, Virginia Tech; Layne Watson, Virginia Tech; Ian Davidson, UC Davis; Richard Helm, Virginia Tech; Naren Ramakrishnan*, Virginia Tech
• Unsupervised Feature Selection for Multi-Cluster Data
  Deng Cai*, Zhejiang University; Chiyuan Zhang, Zhejiang University; Xiaofei He, Zhejiang University
• Unsupervised Transfer Learning: Application to Text Categorization
  Tianbao Yang*, Michigan State University; Rong Jin, Michigan State University; Anil Jain, Michigan State University; Yang Zhou, Michigan State University; Wei Tong, Michigan State University
• UP-Growth: An Efficient Algorithm for High Utility Itemsets Mining
  Vincent Tseng*, National Cheng Kung University; Cheng Wei Wu, National Cheng Kung University; Bai-En Shie, National Cheng Kung University; Philip Yu, University of Illinois at Chicago
• User Browsing Models: Relevance versus Examination
  Ramakrishnan Srikant*, Google Research; Sugato Basu, Google Research; Ni Wang, ; Daryl Pregibon, "Google, USA"
• Versatile Publishing for Privacy Preservation
  Xin Jin*, George Washington University; Mingyang Zhang, George Washington University; Nan Zhang, George Washington University; Gautum Das, UT Arlington
• Why label when you can search? Strategies for applying human resources to build classification models under extreme class imbalance.
  Josh Attenberg*, NYU Polytechnic Institute; Foster Provost, NYU