Matthias Seeger, Max Planck Institute for Biological Cybernetics; David Barber, University College London; Neil Lawrence, University of Manchester; Onno Zoeter, Microsoft Research Cambridge

Beyond Simple Cells: Probabilistic Models for Visual Cortical Processing

Richard Turner, Gatsby Unit, UCL; Pietro Berkes, Brandeis University; Maneesh Sahani, Gatsby Unit, UCL

Efficient Machine Learning - Overcoming Computational Bottlenecks in Machine Learning (Part 1)

Samy Bengio, Google; Corinna Cortes, Google, Inc; Dennis DeCoste, Microsoft; Francois Fleuret, IDIAP Research Institute; Ramesh Natarajan, IBM T.J. Watson Research Center; Edwin Pednault, IBM T.J. Watson Research Center; Dan Pelleg, IBM; Elad Yom-Tov, IBM Haifa Labs

Large Scale Brain Dynamics (Part 1)

Ryan Canolty, UC Berkeley; Kai Miller, University of Washington

Machine Learning for Systems Problems (Part 1)

Archana Ganapathi, University of California, Berkeley; Sumit Basu, Microsoft Research; Fei Sha, University of Southern California; Emre Kiciman, Microsoft Research

Machine Learning for Web Search

Dengyong Zhou, Microsoft Research; Olivier Chapelle, Yahoo!; Thorsten Joachims, Cornell University; Thomas Hofmann, Google Switzerland

Machine Learning in Computational Biology (Part 1)

Gal Chechik, Google; Christina Leslie, Memorial Sloan-Kettering Cancer Center; Quaid Morris, University of Toronto; William Noble, University of Washington; Gunnar Raetsch, Max Planck Society; Koji Tsuda, AIST

Music, Brain and Cognition. Part 1: Learning the Structure of Music and Its Effects On the Brain

David Hardoon, Institute for Infocomm Research; Eduardo Reck-Miranda, University of Plymouth; John Shawe-Taylor, University College London

Principles of Learning Problem Design

John Langford, Yahoo; Alina Beygelzimer, IBM Watson Research Center

Robotics Challenges for Machine Learning

Jan Peters, Max-Planck Institute of Biological Cybernetics; Marc Toussaint, TU Berlin

Topology Learning: New Challenges At the Crossing of Machine Learning,

Michael Aupetit, Commissariat à l'Energie Atomique; Frederic Chazal, INRIA-Futurs; Gilles Gasso, LITIS - INSA de Rouen; David Cohen-Steiner, INRIA Sophia-Antipolis Mediterranee; pierre gaillard, French Atomic Energy Commission

Hierarchical Organization of Behavior: Computational, Psychological and Neural Perspectives (Part 1)

Yael Niv, Princeton University; Matthew Botvinick, Princeton University; Andrew Barto, University of Massachusetts

IBM Student Reception

Efficient Machine Learning - Overcoming Computational Bottlenecks in Machine Learning (Part 2)

Large Scale Brain Dynamics (Part 2)

Ryan Canolty, UC Berkeley; Kai Miller, University of Washington

Machine Learning for Systems Problems (Part 2)

Archana Ganapathi, University of California, Berkeley; Sumit Basu, Microsoft Research; Fei Sha, University of Southern California; Emre Kiciman, Microsoft Research

Machine Learning in Computational Biology (Part 2)

Music, Brain and Cognition. Part 2: Models of Sound and Cognition

Hendrik Purwins, Berlin University of Technology; Xavier Serra, Universitat Pompeu Serra; Klaus Obermayer, Technical University of Berlin

Representations and Inference on Probability Distributions

Kenji Fukumizu, Institute of Statistical Mathematics; Arthur Gretton, CMU and MPI; Alexander Smola, Yahoo! Research

Statistical Network Models

Kevin Murphy, U British Columbia; Lise Getoor, University of Maryland; Eric Xing, Carnegie Mellon University; Raphael Gottardo, University of British Columbia

The Grammar of Vision: Probabilistic Grammar-Based Models for Visual Scene Understanding and Object Categorization

Virginia Savova, Massachusetts Institute of Technology; Josh Tenenbaum, Massachusetts Institute of Technology; Leslie Kaelbling, Massachusetts Institute of Technology; Alan Yuille, UCLA

Mechanisms of Visual Attention

Jillian Fecteau, The Netherlands Institute For Neuroscience; Dirk Walther, University of Illinois at Urbana-Champaign; Vidhya Navalpakkam, Caltech; John Tsotsos, York University

Machine Learning and Games (MALAGA): Open Directions in Applying Machine Learning to Games

Joaquin Quiñonero Candela, Microsoft Research Cambridge (UK); Thore Graepel, Microsoft Research Cambridge (UK); Ralf Herbrich, Future Social Experiences Labs UK

Machine Learning in Adversarial Environments for Computer Security

Richard Lippman, MIT; Pavel Laskov, Fraunhofer FIRST

The Urban Challenge – Perspectives of Autonomous Driving

Sebastian Thrun, Stanford University; Chris Urmson, Carnegie Mellon University; Raul Rojas, Freie Universitaet Berlin; William Uther, NICTA

Hierarchical Organization of Behavior: Computational, Psychological and Neural Perspectives (Part 2)

Yael Niv, Princeton University; Matthew Botvinick, Princeton University; Andrew Barto, University of Massachusetts