On learning from queries and counterexamples in the presence of noise

DOI10.1016/0020-0190(91)90220-CzbMath0714.68062OpenAlexW2083117818WikidataQ124989026 ScholiaQ124989026MaRDI QIDQ751304

Yasubumi Sakakibara

Publication date: 1991

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

Full work available at URL: https://doi.org/10.1016/0020-0190(91)90220-c

zbMATH Keywords

noiseanalysis of algorithmsrandom samplingformal languagesconcept learning

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Formal languages and automata (68Q45)

Related Items (8)

Efficient multiple constraint acquisition ⋮ Exact learning from an honest teacher that answers membership queries ⋮ Learning fallible deterministic finite automata ⋮ Recent advances of grammatical inference ⋮ Grammatical inference: An old and new paradigm ⋮ Learning attribute-efficiently with corrupt oracles ⋮ Learning with unreliable boundary queries ⋮ Improved lower bounds for learning from noisy examples: An information-theoretic approach

Cites Work

• Unnamed Item
• Learning context-free grammars from structural data in polynomial time
• Learning regular sets from queries and counterexamples
• A theory of the learnable

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