Measure Based Regularization

Bousquet, O; Chapelle, O; Hein, M

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Measure Based Regularization

Bousquet, O., Chapelle, O., & Hein, M. (2004). Measure Based Regularization. In S. Thrun, L. Saul, & B. Schölkopf (Eds.), Advances in Neural Information Processing Systems 16 (pp. 1221-1228). Cambridge, MA, USA: MIT Press.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-D8F1-4 Version Permalink: https://hdl.handle.net/21.11116/0000-0005-5375-A

Genre: Conference Paper

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https://papers.nips.cc/paper/2504-measure-based-regularization.pdf (Publisher version) Open Access status unknown

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Creators:
Bousquet, O^{1, 2}, Author
Chapelle, O^{1, 2}, Author
Hein, M^{1, 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 address in this paper the question of how the knowledge of the marginal distribution P(x) can be incorporated in a learning algorithm. We suggest three theoretical methods for taking into account this distribution for regularization and provide links to existing graph-based semi-supervised learning algorithms. We also propose practical implementations.

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Dates: Date issued: 2004-06

Publication Status: Issued

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Identifiers: BibTex Citekey: 2260

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Title: Seventeenth Annual Conference on Neural Information Processing Systems (NIPS 2003)

Place of Event: Vancouver, BC, Canada

Start-/End Date: 2003-12-09 - 2003-12-11

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Title: Advances in Neural Information Processing Systems 16

Source Genre: Proceedings

Creator(s):
Thrun, S, Editor
Saul, LK, Editor
Schölkopf, B¹, Editor

Affiliations:
1 Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794

Publ. Info: Cambridge, MA, USA : MIT Press

Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 1221 - 1228 Identifier: ISBN: 0-262-20152-6