Manifold Denoising

Hein, M; Maier, M

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Manifold Denoising

Hein, M., & Maier, M. (2007). Manifold Denoising. In B. Schölkopf, J. Platt, & T. Hoffman (Eds.), Advances in Neural Information Processing Systems 19 (pp. 561-568). Cambridge, MA, USA: MIT Press.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-CBF1-D Version Permalink: https://hdl.handle.net/21.11116/0000-0002-E21B-1

Genre: Conference Paper

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https://papers.nips.cc/paper/2997-manifold-denoising.pdf (Publisher version) Open Access status unknown

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Creators:
Hein, M^{1, 2}, Author
Maier, 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 consider the problem of denoising a noisily sampled submanifold M in R^d, where the submanifold M
is a priori unknown and we are only given a noisy point sample. The presented denoising algorithm is based
on a graph-based diffusion process of the point sample. We analyze this diffusion process using recent results about
the convergence of graph Laplacians. In the experiments we show that our method is capable of dealing with
non-trivial high-dimensional noise. Moreover using the denoising algorithm as pre-processing method we
can improve the results of a semi-supervised learning algorithm.

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Dates: Date issued: 2007-09

Publication Status: Issued

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Identifiers: BibTex Citekey: 4249

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Title: Twentieth Annual Conference on Neural Information Processing Systems (NIPS 2006)

Place of Event: Vancouver, BC, Canada

Start-/End Date: 2006-12-04 - 2006-12-07

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Title: Advances in Neural Information Processing Systems 19

Source Genre: Proceedings

Creator(s):
Schölkopf, B¹, Editor
Platt, JC, Editor
Hoffman, T, Editor

Affiliations:
1 Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795

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

Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 561 - 568 Identifier: ISBN: 0-262-19568-2