The Perceptron algorithm vs. Winnow: linear vs. logarithmic mistake bounds when few input variables are relevant

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The Perceptron algorithm vs. Winnow: linear vs. logarithmic mistake bounds when few input variables are relevant. / Auer, Peter; Kivinen, J.; Warmuth, M. K.
In: Artificial intelligence, 1997, p. 325-343.

Research output: Contribution to journalArticleResearchpeer-review

Bibtex - Download

@article{42ed2b9fe7844967bcbf222e316bd121,
title = "The Perceptron algorithm vs. Winnow: linear vs. logarithmic mistake bounds when few input variables are relevant",
author = "Peter Auer and J. Kivinen and Warmuth, {M. K.}",
year = "1997",
language = "English",
pages = "325--343",
journal = "Artificial intelligence",
issn = "0004-3702",
publisher = "Elsevier",

}

RIS (suitable for import to EndNote) - Download

TY - JOUR

T1 - The Perceptron algorithm vs. Winnow: linear vs. logarithmic mistake bounds when few input variables are relevant

AU - Auer, Peter

AU - Kivinen, J.

AU - Warmuth, M. K.

PY - 1997

Y1 - 1997

M3 - Article

SP - 325

EP - 343

JO - Artificial intelligence

JF - Artificial intelligence

SN - 0004-3702

ER -