Neural Information Processing Systems

Workshop Information

• The conference brochure is available in either Postscript or LaTeX.
• The workshops will be held on Friday and Saturday, December 4-5 in Breckenridge, CO. Information on accommodations will be posted on the accommodations page as soon as it becomes available.
• Workshop attendees are eligible for special skiing lift ticket rates. See the accommodations page for more information.

Workshop Titles, Links, and Organizers

Friday, December 4

• Olfactory coding: Myths, models and data. [** 2 Day Workshop **] Christiane Linster, Harvard University; Wayne Getz, University of California, Berkeley; Frank Grasso, Boston University.
• Large margin classifiers. [** 2 Day Workshop **] Alex Smola, GMD Berlin; Peter Bartlett, ANU Canberra; Bernhard Schoelkopf, GMD Berlin; Dale Schuurmans, University of Pennsylvania.
• Hybrid neural symbolic integration. [** 2 Day Workshop **] Stefan Wermter, University of Sunderland; Ron Sun, University of Alabama.
• Dynamics in networks of spiking neurons. Wulfram Gerstner, Swiss Federal Institute of Technology.
• Optical imaging of the visual cortex. Ehud Kaplan, Mount Sinai School of Medicine, New York; Gary Blasdel, Harvard Medical School.
• Statistical theories of cortical function. Rajesh P.N. Rao, The Salk Institute; Bruno A. Olshausen, UC Davis; Michael S. Lewicki, The Salk Institute.
• Learning from ambiguous and complex examples. Oded Maron, PHZ Capital Partners; Thomas Dietterich, Oregon State University.
• Turnkey algorithms for improving generalizers. Kagan Tumer and David Wolpert, NASA Ames Research Center.
• Combining supervised and unsupervised learning. Rich Caruana, Just Research; Virginia de Sa, UCSF; Andrew McCallum, Just Research; Michael Kearns, AT&T Laboratories.
• Sequential inference and learning. Mahesan Niranjan, Arnaud Doucet, and Nando de Freitas, Cambridge University.
• Movement primitives: Building blocks for learning motor control. Steve DeWeerth, Georgia Institute of Technology; Stefan Schaal, University of Southern California.
• Simple inference heuristics vs. complex decision machines Peter Todd and Laura Martignon, Max Planck Institute; Kathryn Blackmond Laskey, George Mason University.

Saturday, December 5

• Olfactory coding: Myths, models and data. [** 2 Day Workshop **] Christiane Linster, Harvard University; Wayne Getz, University of California, Berkeley; Frank Grasso, Boston University.
• Large margin classifiers. [** 2 Day Workshop **] Alex Smola, GMD Berlin; Peter Bartlett, ANU Canberra; Bernhard Schoelkopf, GMD Berlin; Dale Schuurmans, University of Pennsylvania.
• Hybrid neural symbolic integration. [** 2 Day Workshop **] Stefan Wermter, University of Sunderland; Ron Sun, University of Alabama.
• Population coding. Glen D. Brown and Kechen Zhang, The Salk Institute.
• Temporal coding: Is there evidence for it and what is its function? Nicho Hatsopoulos and Harel Shouval, Brown University.
• Mining massive databases: Scaling prediction and clustering to massive and high-dimensional data. Usama Fayyad, Microsoft Research; Padhraic Smyth, University of California, Irvine.
• Learning on relational data representations. K. Obermayer, T. Graepel, and R. Herbrich, Technical University of Berlin, Germany.
• Hierarchy and abstraction in reinforcement learning. Ronald Parr, Stanford University; Tom Dietterich, Oregon State University; Leslie Kaelbling, Brown University; Doina Precup, University of Massachusetts, Amherst.
• Development: Building and adapting complex and useful structures . Gary Haith, Stanford; Jeff Elman, UCSD; Silvano Colombano.
• Continuous learning. Peter Protzel, Lars Kindermann, Achim Lwandowski, and Michael Tagscherer, Chemnitz University of Technology, Germany.
• Learning chips and neurobots. Gert Cauwenberghs and Ralph Etienne-Cummings, Johns Hopkins University; Marwan Jabri, University of Sydney.

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