Four types of noise in data for PAC learning

DOI10.1016/0020-0190(95)00016-6zbMath1004.68539OpenAlexW2036478832MaRDI QIDQ673611

Robert H. Sloan

Publication date: 28 February 1997

Published in: Information Processing Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0020-0190(95)00016-6

zbMATH Keywords

noisecomputational learning theorydesign of algorithmsPAC learningconcept learning

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Related Items

Learning under \(p\)-tampering poisoning attacks, Learning with unreliable boundary queries, Learning with restricted focus of attention, Improved lower bounds for learning from noisy examples: An information-theoretic approach

Cites Work

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• Occam's razor
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• Learning in the Presence of Malicious Errors
• A theory of the learnable
• Efficient noise-tolerant learning from statistical queries
• Probability Inequalities for Sums of Bounded Random Variables