Cited by 1,674Machine Learning and AlgorithmsComplexity and Algorithms in Graphssemigroups and automata theory

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Boosting a Weak Learning Algorithm by Majority

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Freund, Y.·1995·Information and Computation

DOI 10.1006/inco.1995.1136

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Authors: Freund, Y.
Affiliations: AT&T (United States) (US)
Corresponding author: Freund, Y.
ORCID: Freund, Y.
Venue: Information and Computation
Publisher: Elsevier BV
Published: 1995-09
Volume: 121
Issue: 2
Pages: 256-285
ISSN: 0890-5401 (ISSN-L)
DOI: 10.1006/inco.1995.1136
OpenAlex: W2070534370
Cited by: 1,674
References: 0
Citations by year: 2026: 30 · 2025: 54 · 2024: 64 · 2023: 70 · 2022: 68 · 2021: 82 · 2020: 72 · 2019: 79 · 2018: 55 · 2017: 57 · 2016: 55 · 2015: 59 · 2014: 56 · 2013: 68 · 2012: 67
FWCI: 15.27
Type: journal article
Language: en
Open access: bronze
doi.org
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
www.elsevier.com/open-access/userlicense/1.0/ (vor, 6529 d)
Locations: Information and Computation (publishedVersion)
Topics: Physical Sciences › Computer Science › Artificial Intelligence › Machine Learning and Algorithms
Physical Sciences › Computer Science › Computational Theory and Mathematics › Complexity and Algorithms in Graphs
Physical Sciences › Computer Science › Computational Theory and Mathematics › semigroups and automata theory
Keywords: boosting, weak learning, majority voting, PAC learning, learnability, threshold circuits, power of representation, generalization bounds

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