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  Falsification and future performance

Balduzzi, D. (2011). Falsification and future performance. In Solomonoff 85th Memorial Conference (pp. 1-13). Berlin, Germany: Springer.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-B8D6-8 Version Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-B8D7-6
Genre: Conference Paper

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Balduzzi, D1, Author           
Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              

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 Abstract: We information-theoretically reformulate two measures of capacity from statistical learning theory: empirical VC-entropy and empirical Rademacher complexity. We show these capacity measures count the number of hypotheses about a dataset that a learning algorithm falsies when it nds the classier in its repertoire minimizing empirical risk. It then follows from that the future performance of predictors on unseen data is controlled in part by how many hypotheses the learner falsies. As a corollary we show that empirical VC-entropy quanties the message length of the true hypothesis in the optimal code of a particular probability distribution, the so-called actual repertoire.

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 Dates: 2011-12
 Publication Status: Issued
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 Identifiers: URI: http://www.solomonoff85thmemorial.monash.edu/
BibTex Citekey: Balduzzi2011_3
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Title: Solomonoff 85th Memorial Conference
Place of Event: Melbourne, Australia
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Title: Solomonoff 85th Memorial Conference
Source Genre: Proceedings
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Publ. Info: Berlin, Germany : Springer
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 1 - 13 Identifier: -