Theory revision with queries: Horn, read-once, and parity formulas
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Publication:814598
DOI10.1016/j.artint.2004.01.002zbMath1085.68071OpenAlexW1970275339MaRDI QIDQ814598
Balázs Szörényi, Robert H. Sloan, György Turán, Judy Goldsmith
Publication date: 7 February 2006
Published in: Artificial Intelligence (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.artint.2004.01.002
Computational learning theoryHorn formulasKnowledge revisionBoolean function learningQuery learningTheory revision
Related Items (3)
Revising threshold functions ⋮ Projective DNF formulae and their revision ⋮ Explaining AI decisions using efficient methods for learning sparse Boolean formulae
Cites Work
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- Combinatorial characterization of read-once formulae
- Fast learning of \(k\)-term DNF formulas with queries.
- Learning regular sets from queries and counterexamples
- Functions computed by monotone Boolean formulas with no repeated variables
- Structure identification in relational data
- Lower bound methods and separation results for on-line learning models
- Learning conjunctions of Horn clauses
- Complexity theoretic hardness results for query learning
- Attribute-efficient learning in query and mistake-bound models
- Theory refinement combining analytical and empirical methods
- Knowledge-based artificial neural networks
- Logical settings for concept-learning
- Adaptive versus nonadaptive attribute-efficient learning
- The complexity of theory revision
- When won't membership queries help?
- Asking questions to minimize errors
- Structural results about on-line learning models with and without queries
- Projection learning
- Effective and efficient knowledge base refinement
- Queries and concept learning
- Exact learning Boolean functions via the monotone theory
- Read-twice DNF formulas are properly learnable
- More theory revision with queries (extended abstract)
- Linear-time algorithms for testing the satisfiability of propositional horn formulae
- Learning read-once formulas with queries
- The Semantics of Predicate Logic as a Programming Language
- The complexity of revising logic programs
- Cryptographic limitations on learning Boolean formulae and finite automata
- Learning Theory and Kernel Machines
- On the Uniform Convergence of Relative Frequencies of Events to Their Probabilities
- On sentences which are true of direct unions of algebras
- The decision problem for some classes of sentences without quantifiers
- Theory revision with queries: DNF formulas
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