The annual Neural Information Processing Systems Workshops bring together scientists with broadly varying backgrounds in statistics, mathematics, computer science, physics, electrical engineering, neuroscience, and cognitive science, unified by a common desire to develop novel computational and statistical strategies for information processing and to understand the mechanisms for information processing in the brain. As opposed to conferences, these workshops maintain a flexible format that encourages the presentation and discussion of work in progress. The workshops serve as an incubator for the development of important new ideas in this rapidly evolving field. The Series Editors, in consultation with workshop organizers and members of the NIPS Foundation Board, select specific workshop topics on the basis of scientific excellence, intellectual breadth, and technical impact. Collections of papers chosen and edited by the organizers of specific workshops are built around pedagogical introductory chapters, while research monographs provide comprehensive descriptions of workshop-related topics, to create a series of books that provides a timely, authoritative account of the latest developments in the exciting field of neural computation.
For further information about the Series contact:
Michael I. Jordan jordan@cs.berkeley.edu
Thomas G. Dietterich tgd@eecs.oregonstate.edu
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Theory and Practice
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Advances in Large-Margin Classifiers
Peter J. Bartlett, Bernhard Schölkopf, Dale Schuurmans and
Alex J Smola (Eds.)
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Advances in Minimum Description Length Theory and Applications
Peter D. Grünwald,
In Jae Myung and Mark A. Pitt (Eds.)
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Exploratory Analysis and Data Modeling in Functional Neuroimaging
Friedrich T. Sommer
and Andrzej Wichert
(Eds.)
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Nearest-Neighbor Methods in Learning and Vision Theory and Practice
Gregory Shakhnarovich,
Piotr Indyk and Trevor
Darrell (Eds.)
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Probabilistic Models of the Brain Perception and Neural Function
Rajesh P. N. Rao,
Bruno A. Olshausen and Michael S. Lewicki (Eds.) |