| SESSION NAME | DAY | SESSION ID | TITLE | AUTHORS |
| KEYNOTE TALK | MON | K1 | Convex Optimization: from Embedded Real-Time to Large-Scale Distributed | Stephen Boyd, Stanford |
| CLASSIFICATION | MON | A1 | CHIRP: A new classifier based on Composite Hypercubes on Iterated Random Projections | Leland Wilkinson, Systat; Anushka Anand*, UIC; Tuan Dang, UIC |
| MON | A1 | Supervised Learning for Provenance-Similarity of Binaries | Sagar Chaki*, Carnegie Mellon University; Cory Cohen, ; Arie Gurfinkel, |
| MON | A1 | Trading Representability for Scalability: Adaptive Multi-Hyperlane Machine for Nonlinear Classification | Zhuang Wang*, Siemens; Nemanja Djuric, ; Koby Crammer, ; Slobodan Vucetic, |
| MON | A1 | An Improved GLMNET for L1-regularized Logistic Regression | Guo-Xun Yuan, National Taiwan University; Chia-Hua Ho, National Taiwan University; Chih-Jen Lin*, National Taiwan University |
| WEB USER MODELING | MON | A2 | Scalable Inference of Dynamic User Interests for Behavioural Targeting | Amr Ahmed*, Carnegie Mellon University; Yucheng Low, Carnegie Mellon University; Mohamed Aly, Yahoo Research; Vanja Josifovski , Yahoo! Research; Alex Smola, Yahoo! Research |
| MON | A2 | Multiple Domain User Personalization | Yucheng Low*, Carnegie Mellon University; Alex Smola, Yahoo and ANU; Deepak Agarwal, |
| MON | A2 | Click Shaping to Optimize Multiple Objectives | Xuanhui Wang, Yahoo! Labs; Deepak Agarwal*, ; Bee-Chung Chen, Yahoo! Research; Pradheep Elango, |
| MON | A2 | Response prediction using collaborative filtering with hierarchies and side-information | Aditya Menon*, UC San Diego; Krishna-Prasad Chitrapura, Yahoo! Labs Bangalore; Sachin Garg, Yahoo! Labs Bangalore; Deepak Agarwal, Yahoo! Research; Nagaraj Kota, Yahoo! Labs Bangalore
|
| KEYNOTE TALK | MON | K2 | Internet Scale Data Analysis | Peter Norvig, Google |
| TEXT MINING | MON | B1 | Beyond Keyword Search: Discovering Relevant Scientific Literature | Khalid El-arini*, Carnegie Mellon University; Carlos Guestrin, CMU |
| MON | B1 | Collaborative Topic Models for Recommending Scientific Articles | Chong Wang*, Princeton University; David Blei, Princeton Univ |
| MON | B1 | Partially Labeled Topic Models for Interpretable Text Mining | Daniel Ramage*, Stanford University; Christopher Manning, Stanford University; Susan Dumais, Microsoft Research |
| SOCIAL NETWORKS | MON | B2 | On the Semantic Annotation of Places in Location-based Social Networks | Mao Ye*, PSU; Dong Shou, ; Wang-Chien Lee, ; Peifeng Yin, ; Krzysztof Janowicz, |
| MON | B2 | Sparsification of Influence Networks | Michael Mathioudakis*, University of Toronto; Francesco Bonchi, Yahoo! Research; Carlos Castillo, Yahoo!; Aristides Gionis, Yahoo! Research Barcelona; Antti Ukkonen, |
| MON | B2 | Leveraging Collaborative Tagging for Web Item Design | Mahashweta Das*, UTA; Gautam Das, UT Arlington; Vagelis Hristidis, Florida International University |
| TEXT MINING | MON | C1 | Latent Topic Feedback for Information Retrieval | David Andrzejewski*, Lawrence Livermore National La; David Buttler, Lawrence Livermore National Laboratory |
| MON | C1 | Locality-Sensitive Factor Models for Multi-Context Recommendation | Deepak Agarwal*, ; Bee-Chung Chen, Yahoo! Research; Bo Long, |
| MON | C1 | Latent Aspect Rating Analysis without Aspect Keyword Supervision | Hongning Wang*, UIUC; Yue Lu, University of Illinois; ChengXiang Zhai, UIUC |
| SCALABILITY | MON | C2 | Fast Clustering using MapReduce | Alina Ene, University of Illinois at Urbana-Champaign; Sungjin Im*, University of Illinois; Benjamin Moseley, University of Illinois at Urbana-Champaign |
| MON | C2 | Clustering Very Large Multi-dimensional Datasets with MapReduce | Robson Leonardo Ferreira Cordeiro*, ICMC-USP-Brazil; Caetano Traina Jr., ICMC-USP; Agma Juci Machado Traina, ICMC-USP; Julio López, SCS-CMU; U Kang, Carnegie Mellon University; Christos Faloutsos, CMU |
| MON | C2 | Selective Block Minimization for Faster Convergence of Limited Memory Large-scale Linear Models | Kai-Wei Chang*, UIUC; Dan Roth, University of Illinois at Urbana-Champaign |
| KEYNOTE TALK | TUE | K3 | Cancer Genomics | David Haussler, UC Santa Cruz |
| MATRIX FACTORIZATION | TUE | A1 | Integrating Low-Rank and Group-Sparse Structures for Robust Multi-Task Learning | Jianhui Chen*, Arizona State University; Jiayu Zhou, Arizona State University; Jieping Ye, Arizona State University |
| TUE | A1 | Model Order Selection for Boolean Matrix Factorization | Pauli Miettinen*, MPI Informatics; Jilles Vreeken, University of Antwerp, Belgium |
| TUE | A1 | Rank Aggregation via Nuclear Norm Minimization | David Gleich*, Sandia National Laboratories; Lek-Heng Lim, University of Chicago |
| TUE | A1 | Large-Scale Matrix Factorization with Distributed Stochastic Gradient Descent | Rainer Gemulla*, Max-Planck Institut; Peter Haas, IBM Almaden; Erik Nijkamp, IBM Almaden; Yannis Sismanis, IBM Almaden |
| USER MODELING | TUE | A2 | From Bias to Opinion: A Transfer-Learning Approach to Sentiment Analysis | Pedro Henrique Guerra*, UFMG; Adriano Veloso, UFMG; Wagner Meira Junior, UFMG; Virgilio Almeida, UFMG |
| TUE | A2 | User Reputation in a Comment Rating Environment | Bee-Chung Chen*, Yahoo! Research; Belle Tseng, Yahoo! Labs; Jie Yang, Yahoo! Labs; Jian Guo, University of Michigan |
| TUE | A2 | Selecting a Comprehensive Set of Reviews | Panayiotis Tsaparas*, Microsoft Research; Alexandros Ntoulas, Microsoft Research; Evimaria Terzi, Boston University |
| KEYNOTE TALK | TUE | K4 | The Mathematics of Causal Inference | Judea Pearl, UCLA |
| TEXT MINING | TUE | B1 | Refining causality: who copied from whom? | Tristan Snowsill*, University of Bristol; Nick Fyson, University of Bristol; Tijl De Bie, University of Bristol; Nello Cristianini, University of Bristol |
| TUE | B1 | Conditional Topical Coding: an Efficient Topic Model Conditioned on Rich Features | Jun Zhu*, Carnegie Mellon University; Ni Lao, Carnegie Mellon University; Ning Chen, Tsinghua University; Eric Xing, CMU |
| TUE | B1 | Tracking Trends: Incorporating Term Volume into Temporal Topic Models | Liangjie Hong*, Lehigh University; Dawei Yin, lehigh University; Jian Guo, University of Michigan; Brian Davison, Lehigh University |
| THEORY | TUE | B2 | Stackelberg Games for Adversarial Prediction Problems | Michael Brückner*, University of Potsdam; Tobias Scheffer, University of Potsdam |
| TUE | B2 | Leakage in Data Mining: Formulation, Detection, and Avoidance | Claudia Perlich*, Media6Degrees; Shachar Kaufman, Tel-Aviv University; Saharon Rosset, Tel Aviv University |
| TUE | B2 | An information theoretic framework for data mining | Tijl De Bie*, University of Bristol |
| UNSUPERVISED LEARNING | TUE | C1 | Density Estimation Trees | Parikshit Ram*, Geogia Institute of Technology; Alexander Gray, Georgia Tech |
| TUE | C1 | Unsupervised Clustering of Multidimensional Distributions using Earth Mover Distance | David Applegate, AT&T Labs - Research; Tamraparni Dasu*, AT&T Labs; Shankar Krishnan, AT&T Labs - Research; Simon Urbanek, AT&T Labs - Research |
| TUE | C1 | Online heterogeneous mixture modeling with marginal and copula selection | RYOHEI FUJIMAKI*, NEC Laboratories America; Yasuhiro Sogawa, ; Satosi Morinaga, |
| PREDICTIVE MODELING | TUE | C2 | Bounded Coordinate-Descent for Biological Sequence Classification in High Dimensional Predictor Space | Georgiana Ifrim*, Bioinformatics Research Centre; Carsten Wiuf, Bioinformatics Research Centre |
| TUE | C2 | Multi-Source Domain Adaptation and Its Application to Early Detection of Fatigue | Rita Chattopadhyay, Arizona State University; Jieping Ye*, Arizona State University; Sethuraman Panchanathan, Arizona State University; Wei Fan, Columbia; Ian Davidson, UC Davis |
| TUE | C2 | Two-locus association mapping in subquadratic runtime | Panagiotis Achlioptas, ; Bernhard Schölkopf, Max Planck Institute; Karsten Borgwardt*, Max Planck Institutes T?bingen |
| SIGKDD BUSINESS MEETING | WED | K5 | | | |
| GRAPH ANALYSIS | WED | A1 | Diversity in ranking via resistive graph centers | Kumar Dubey*, IBM Research; Soumen Chakrabarti, "Indian Institute of Technology, Bombay"; Chiru Bhattacharya, IISc |
| WED | A1 | Collective Graph Identification | Galileo Namata*, University of Maryland; Stanley Kok, University of Maryland; Lise Getoor, "University of Maryland, College Park" |
| WED | A1 | Semi-Supervised Ranking on Very Large Graph with Rich Metadata | Bin Gao*, Microsoft Research Asia; Tie-Yan Liu, Microsoft Research Asia; Wei Wei, ; Taifeng Wang, Microsft research; Hang Li, Microsoft |
| WED | A1 | Benefits of Bias: Towards Better Characterization of Network Sampling | Arun Maiya*, UIC; Tanya Berger-Wolf, University of Illinois at Chicago |
| ONLINE DATA AND STREAMS | WED | A2 | Enabling Fast Prediction for Ensemble Models on Data Streams | Byron Gao*, Texas State University; Peng Zhang, Chinese Academy of Sciences; Xingquan Zhu, University of Technology, Sydney |
| WED | A2 | Online Active Inference and Learning | Joshua Attenberg*, NYU Polytechnic Institute; Foster Provost, NYU |
| WED | A2 | Unbiased Online Active Learning in Data Streams | Wei Chu*, Yahoo! Labs; Martin Zinkevich, Yahoo Research; Lihong Li, Yahoo! Research; Achint Thomas, Yahoo! Labs; Belle Tseng, Yahoo! Labs |
| WED | A2 | Learning to Trade Off Between Exploration and Exploitation in Multiclass Bandit Prediction | Hamed Valizadegan*, University of Pittsburgh; Rong Jin, Michigan State University; Shijun Wang, National Institute of Health |
| PANEL | WED | K6 | Lessons learned from contests in data mining | Moderator: Charles Elkan, UCSD; Speakers: Jeremy Howard (Kaggle), Yehuda Koren (Yahoo!), Tie-Yan Liu (Microsoft Research), Claudia Perlich (Media6Degrees) |
| PRIVACY | WED | B1 | Differentially Private Data Release for Data Mining | Noman Mohammed*, Concordia University; Rui Chen, Concordia University; Benjamin Fung, Concordia University; Mourad Debbabi, Concordia University; Philip Yu, University of Illinois at Chicago |
| WED | B1 | k-NN as an Implementation of Situation Testing for Discrimination Discovery and Prevention | Binh Thanh Luong, Institute for Advanced Studies; Salvatore Ruggieri*, University of Pisa; Franco Turini, University of Pisa |
| WED | B1 | Exploiting Vulnerability to Secure User Privacy on Social Networking Site | Pritam Gundecha*, Arizona State University; Geoffrey Barbier, ASU; Huan Liu, |
| FREQUENT SETS | WED | B2 | Tell me what I need to know: succinctly summarizing data with itemsets | Michael Mampaey*, Universiteit Antwerpen; Jilles Vreeken, University of Antwerp, Belgium; Nikolaj Tatti, University of Antwerp |
| WED | B2 | Direct Local Pattern Sampling by Efficient Two-Step Random Procedures | Mario Boley*, Fraunhofer IAIS; Claudio Lucchese, "ISTI - CNR, Italy"; Daniel Paurat, University Bonn; Thomas Gärtner, University Bonn |
| WED | B2 | Mining Frequent Closed Graphs on Evolving Data Streams | Albert Bifet*, University of Waikato; Geoff Holmes, University of Waikato; Bernhard Pfahringer, University of Waikato; Ricard Gavaldà, UPC-Barcelona Tech |
| GRAPH MINING | WED | C1 | Dual Active Feature and Sample Selection for Graph Classification | Xiangnan Kong, Univ of Illinois at Chicago; Wei Fan, Columbia; Philip Yu*, University of Illinois at Chicago |
| WED | C1 | It's Who You Know: Graph Mining Using Recursive Structural Features | Keith Henderson, Lawrence Livermore National Laboratory; Brian Gallagher, Lawrence Livermore National Laboratory; Lei Li, Carnegie Mellon University; Leman Akoglu, Carnegie Mellon University; Tina Eliassi-Rad*, LLNL; Hanghang Tong, IBM Research; Christos Faloutsos, CMU |
| WED | C1 | Triangle Listing in Massive Networks and Its Applications | Shumo Chu*, NTU, Singapore; James Cheng, NTU, Singapore |
