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  A Note on Parameter Tuning for On-Line Shifting Algorithms

Bousquet, O.(2003). A Note on Parameter Tuning for On-Line Shifting Algorithms. Tübingen, Germany: Max Planck Institute for Biological Cybernetics.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-DDF2-F Version Permalink: http://hdl.handle.net/21.11116/0000-0002-8D0E-1
Genre: Report

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Bousquet, O1, 2, Author              
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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: In this short note, building on ideas of M. Herbster [2] we propose a method for automatically tuning the parameter of the FIXED-SHARE algorithm proposed by Herbster and Warmuth [3] in the context of on-line learning with shifting experts. We show that this can be done with a memory requirement of O(nT) and that the additional loss incurred by the tuning is the same as the loss incurred for estimating the parameter of a Bernoulli random variable.

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 Dates: 2003-01
 Publication Status: Published in print
 Pages: 9
 Publishing info: Tübingen, Germany : Max Planck Institute for Biological Cybernetics
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 Identifiers: BibTex Citekey: 2294
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Title: Technical Report of the Max Planck Institute for Biological Cybernetics
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