ICML Program Chairs

Lise Getoor :   University of Maryland
Tobias Scheffer :  University of Potsdam

Area Chairs

Yasemin Altun: Max Planck Institute for Biological Cybernetics ----
Semi-supervised Learning
Xiaojin Zhu: University of Wisconsin-Madison ---- Semi-supervised Learning
Ulf Brefeld:   Yahoo! Research -----  Structured Output Prediction
Thorsten Joachims: Cornell University ---- Structured Output Prediction
Thomas Gaertner: University of Bonn & Fraunhofer IAIS ---- Graph Mining
Stefan Wrobel: Fraunhofer IAIS --- Data Streams
Shie Mannor: Technion ---- Reinforcement Learning
Shai Shalev-Schwartz: Hebrew University of Jerusalem --- Optimization Algorithms
Sathiya Keerthi: Yahoo! Research ---- Optimization Algorithms
Sally Goldman: Washington University ---- Learning theory
Ruslan Salakhutdinov: University of Toronto --- Neural networks, Deep Learning
Olivier Chapelle: Yahoo! Research ---- Applications
Nathan Srebro: University of Chicago --- Statistical Methods
Dale Schuurmans: University of Alberta --- Unsupervised Learning and
Outlier Detection
Csaba Szepesvari: University of Alberta --- Partially observable
Markov Decision Processes
Corinna Cortes: Google --- Kernel Methods
Charles Elkan: UC San Diego --- Cost-sensitive Learning
Carla Brodley: Tufts University ---  Active Learning
Bernhard Pfahringer: University of Waikato--- Empirical Insights into ML
Ben Taskar: University of Pennsylvania --- Supervised Learning
Arthur Gretton: Max Planck Institute for Biological Cybernetics ---
Causal Inference
Alexandru Niculescu-Mizil: NEC Labs America --- Time-series analysis
Michelle Sebag: Universite Paris Sud --- Evolutionary Computation
Mattias Seeger: University of Saarland --- Gaussian Processes
Martin Zinkevich: University of Alberta --- Game Theory
Kurt Driessens: KU Leuven --- Reinforcement Learning
Kristian Kersting: Fraunhofer IAIS and Univeristy of Bonn
---Statistical Relational Learning
Kiri Wagstaff: JPL, Caltech -- Clustering
Kilian Weinberger: Washington University in St Louis -- Transfer and
multi-task learning
Katharina Morik: University of Dortmund --- Feature selection and
dimensionality reduction
Kai Yu: NEC Labs --- Bayesian inference
John Langford: Yahoo! Research --- Active Learning
Johannes Fuernkranz: University of Darmstadt --- Ranking and preference learning
Joelle Pineau: McGill University --- Reinforcement Learning
Jennifer Neville: Purdue University --- Social Network Analysis
Hal Daume III: University of Maryland --- Natural Language Processing
Guy Lebanon: Georgia Tech --- Geometric Approaches
Francis Bach: INRIA --- Sparsity and Compressed Sensing
Filip Radlinski: Microsoft Research, Cambridge --- Information Retrieval
Fei Sha: University of Southern California ---  Feature Selection &
Dimensionality Reduction
Eric Xing: Carnegie-Mellon University ---Graph-Based Learning Methods
David McAllester: Toyota Tech Institute Chicago --- Latent Variable
and Topic Models
David Blei: Princeton University --- Latent Variable and Topic Models