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  Kernel Measures of Conditional Dependence

Fukumizu, K., Gretton, A., Sun, X., & Schölkopf, B. (2008). Kernel Measures of Conditional Dependence. In C. Platt, D. Koller, Y. Singer, & S. Roweis (Eds.), Advances in Neural Information Processing Systems 20: 21st Annual Conference on Neural Information Processing Systems 2007 (pp. 489-496). Red Hook, NY, USA: Curran.

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 Creators:
Fukumizu, K, Author           
Gretton, A1, 2, Author           
Sun, X1, 2, Author           
Schölkopf, B1, 2, Author           
Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 Abstract: We propose a new measure of conditional dependence of random variables, based on normalized cross-covariance operators on reproducing kernel Hilbert spaces. Unlike previous kernel dependence measures, the proposed criterion does not depend on the choice of kernel in the limit of infinite data, for a wide class of kernels. At the same time, it has a straightforward empirical estimate with good convergence behaviour. We discuss the theoretical properties of the measure, and demonstrate its application in experiments.

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 Dates: 2008-09
 Publication Status: Published in print
 Pages: -
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 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: 4914
 Degree: -

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Title: Twenty-First Annual Conference on Neural Information Processing Systems (NIPS 2007)
Place of Event: Vancouver, BC, Canada
Start-/End Date: 2007-12-03 - 2007-12-06

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Title: Advances in Neural Information Processing Systems 20: 21st Annual Conference on Neural Information Processing Systems 2007
Source Genre: Proceedings
 Creator(s):
Platt, C, Editor
Koller, D, Editor
Singer, Y, Editor
Roweis, ST, Editor
Affiliations:
-
Publ. Info: Red Hook, NY, USA : Curran
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 489 - 496 Identifier: ISBN: 978-1-605-60352-0