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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
  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
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
  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
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
  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
  Structured Output Prediction
David Blei
  Princeton University
  Latent Variable and Topic Models