Learning definite Horn formulas from closure queries
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Publication:507524
DOI10.1016/j.tcs.2015.12.019zbMath1356.68114arXiv1503.09025OpenAlexW2210079048MaRDI QIDQ507524
Cristina Tîrnăucă, José L. Balcázar, Marta Arias
Publication date: 6 February 2017
Published in: Theoretical Computer Science (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1503.09025
Computational learning theory (68Q32) Logic in computer science (03B70) Galois correspondences, closure operators (in relation to ordered sets) (06A15)
Related Items (4)
From equivalence queries to PAC learning: the case of implication theories ⋮ Learning a propagation complete formula ⋮ Bounds on the size of PC and URC formulas ⋮ Probably approximately correct learning of Horn envelopes from queries
Cites Work
- Construction and learnability of canonical Horn formulas
- Necessary and sufficient conditions for learning with correction queries
- Learning conjunctions of Horn clauses
- Attribute exploration with background knowledge
- A theory of finite closure spaces based on implications
- Learning from examples with unspecified attribute values.
- When won't membership queries help?
- Queries and concept learning
- A general dimension for query learning
- Reasoning with models
- A Note on the Relationship between Different Types of Correction Queries
- Learning DFA from Correction and Equivalence Queries
- Canonical Horn Representations and Query Learning
- Linear-time algorithms for testing the satisfiability of propositional horn formulae
- Minimum Covers in Relational Database Model
- On sentences which are true of direct unions of algebras
- The decision problem for some classes of sentences without quantifiers
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