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  Intrinsic Dimensionality Estimation of Submanifolds in Rd

Hein, M., & Audibert, J.-Y. (2005). Intrinsic Dimensionality Estimation of Submanifolds in Rd. In S. Dzeroski, L. de Raedt, & S. Wrobel (Eds.), ICML '05: 22nd international conference on Machine learning (pp. 289-296). New York, NY, USA: ACM Press.

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 Creators:
Hein, M1, 2, Author           
Audibert, J-Y, 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 present a new method to estimate the intrinsic dimensionality of a submanifold M in Euclidean space from random samples. The method is based on the
convergence rates of a certain U-statistic on the manifold. We solve at least partially the question of the choice of the scale of the data.
Moreover the proposed method is easy to implement, can handle large data sets and performs very well even for small sample sizes. We compare the
proposed method to two standard estimators on several artificial as well as real data sets.

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 Dates: 2005-08
 Publication Status: Issued
 Pages: -
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 Identifiers: BibTex Citekey: 3470
DOI: 10.1145/1102351.1102388
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Title: 22nd International Conference on Machine Learning (ICML 2005)
Place of Event: Bonn, Germany
Start-/End Date: 2005-08-07 - 2005-08-11

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Title: ICML '05: 22nd international conference on Machine learning
Source Genre: Proceedings
 Creator(s):
Dzeroski, S, Editor
de Raedt, L, Editor
Wrobel, S, Editor
Affiliations:
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Publ. Info: New York, NY, USA : ACM Press
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 289 - 296 Identifier: ISBN: 1-59593-180-5