Neural Information Processing series

The yearly Neural Information Processing Systems (NIPS) 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. 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.

Series editor: Michael I. Jordan and Thomas Dietterich

Dataset Shift in Machine Learning

Joaquin Quiñonero-Candela, Masashi Sugiyama, Anton Schwaighofer, Neil D. Lawrence

Jun 07, 2022

An Introduction to Lifted Probabilistic Inference

Guy Van den Broeck, Kristian Kersting, Sriraam Natarajan, David Poole

Aug 17, 2021

Log-Linear Models, Extensions, and Applications

Aleksandr Aravkin, Anna Choromanska, Li Deng, Georg Heigold, Tony Jebara, Dimitri Kanevsky, Stephen J. Wright

Nov 27, 2018

Perturbations, Optimization, and Statistics

Tamir Hazan, George Papandreou, Daniel Tarlow

Dec 23, 2016

Advanced Structured Prediction

Sebastian Nowozin, Peter V. Gehler, Jeremy Jancsary, Christoph H. Lampert

Dec 05, 2014

Practical Applications of Sparse Modeling

Irina Rish, Guillermo A. Cecchi, Aurelie Lozano, Alexandru Niculescu-Mizil

Sep 12, 2014

Optimization for Machine Learning

Suvrit Sra, Sebastian Nowozin, Stephen J. Wright

Sep 30, 2011

Learning Machine Translation

Cyril Goutte, Nicola Cancedda, Marc Dymetman, George Foster

Nov 14, 2008

Large-Scale Kernel Machines

Léon Bottou, Olivier Chapelle, Dennis DeCoste, Jason Weston

Aug 17, 2007

Predicting Structured Data

Gökhan BakIr, Thomas Hofmann, Bernhard Schölkopf, Alexander J. Smola, Ben Taskar, S.V.N Vishwanathan

Jul 27, 2007

Toward Brain-Computer Interfacing

Guido Dornhege, José del R. Millán, Thilo Hinterberger, Dennis J. McFarland, Klaus-Robert Müller

Jul 20, 2007

New Directions in Statistical Signal Processing

Simon Haykin, Jose C. Principe, Terrence J. Sejnowski, John McWhirter

Oct 13, 2006

Nearest-Neighbor Methods in Learning and Vision

Gregory Shakhnarovich, Trevor Darrell, Piotr Indyk

Mar 24, 2006

Advances in Minimum Description Length

Peter D. Grünwald, Jay Injae Myung, Mark A. Pitt

Feb 25, 2005

Exploratory Analysis and Data Modeling in Functional Neuroimaging

Friedrich T. Sommer, Andrzej Wichert

Nov 08, 2002

Probabilistic Models of the Brain

Rajesh P.N. Rao, Bruno A. Olshausen, Michael S. Lewicki

Mar 29, 2002

Advanced Mean Field Methods

Manfred Opper, David Saad

Jun 08, 2001

Advances in Large-Margin Classifiers

Alexander J. Smola, Peter Bartlett, Bernhard Schölkopf, Dale Schuurmans

Sep 29, 2000