Necessary and sufficient conditions for learning with correction queries
From MaRDI portal
Publication:1034636
DOI10.1016/j.tcs.2009.09.004zbMath1194.68197OpenAlexW1990396064MaRDI QIDQ1034636
Cristina Tîrnăucă, Satoshi Kobayashi
Publication date: 6 November 2009
Published in: Theoretical Computer Science (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.tcs.2009.09.004
Learning and adaptive systems in artificial intelligence (68T05) Formal languages and automata (68Q45)
Related Items (1)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Learning context-free grammars from structural data in polynomial time
- Algorithmic learning theory. 18th international conference, ALT 2007, Sendai, Japan, October 1--4, 2007. Proceedings
- Grammatical inference: Algorithms and applications. 9th international colloquium, ICGI 2008, Saint-Malo, France, September 22--24, 2008. Proceedings
- Learning regular sets from queries and counterexamples
- Finding patterns common to a set of strings
- Formal languages and applications.
- Characterizations of monotonic and dual monotonic language learning
- Queries and concept learning
- Formal language identification: query learning vs. gold-style learning
- A general comparison of language learning from examples and from queries
- Relations between Gold-style learning and query learning
- One-Shot Learners Using Negative Counterexamples and Nearest Positive Examples
- On Learning Regular Expressions and Patterns Via Membership and Correction Queries
- A Note on the Relationship between Different Types of Correction Queries
- Learning DFA from Correction and Equivalence Queries
- Inductive inference of formal languages from positive data
- Inference of Reversible Languages
- Learning Theory
- Algorithmic Learning Theory
- Grammatical Inference: Algorithms and Applications
- Language identification in the limit
- Machines, Computations, and Universality
- Theory and Applications of Models of Computation
This page was built for publication: Necessary and sufficient conditions for learning with correction queries
