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  Active Learning for Parzen Window Classifier

Chapelle, O. (2005). Active Learning for Parzen Window Classifier. In R. Cowell, & Z. Ghahramani (Eds.), AISTATS 2005: Tenth International Workshop onArtificial Intelligence and Statistics (pp. 49-56). The Society for Artificial Intelligence and Statistics.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-D689-2 Version Permalink: https://hdl.handle.net/21.11116/0000-0005-3A7D-F
Genre: Conference Paper

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http://www.gatsby.ucl.ac.uk/aistats/aistats2005_eproc.pdf (Any fulltext)
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 Creators:
Chapelle, O1, 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: The problem of active learning is approached in this paper by minimizing
directly an estimate of the expected test error. The main difficulty
in this ``optimal'' strategy is that output probabilities need to be
estimated accurately. We suggest here different methods
for estimating those efficiently.
In this context, the Parzen window classifier is considered
because it is both simple and probabilistic. The analysis of experimental
results highlights that regularization is a key ingredient for this strategy.

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 Dates: 2005-01
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: 2563
 Degree: -

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Title: Tenth International Workshop on Artificial Intelligence and Statistics (AI Statistics 2005)
Place of Event: Barbados
Start-/End Date: 2005-01-06 - 2005-01-08

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Title: AISTATS 2005: Tenth International Workshop onArtificial Intelligence and Statistics
Source Genre: Proceedings
 Creator(s):
Cowell, R, Editor
Ghahramani, Z, Editor
Affiliations:
-
Publ. Info: The Society for Artificial Intelligence and Statistics
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 49 - 56 Identifier: ISBN: 0-9727358-1-X