Abstract
Learning of monotone functions is a well-known problem. Results obtained by V. K. Korobkov and G. Hansel imply that the complexity φM(n) of learning of monotone Boolean functions equals
Note: Originally published in Diskretnaya Matematika (2019) 31, №4, 53–69 (in Russian).
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Funding: Research was partially supported by RFBR, project 19-01-00200-a.
References
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Articles in the same Issue
- Frontmatter
- On the action of the implicative closure operator on the set of partial functions of the multivalued logic
- Bounds on Shannon functions of lengths of contact closure tests for contact circuits
- Conditions of A-completeness for linear automata over dyadic rationals
- Learning of monotone functions with single error correction
- Multitype weakly subcritical branching processes in random environment
- Convex algebras of probability distributions induced by finite associative rings
Articles in the same Issue
- Frontmatter
- On the action of the implicative closure operator on the set of partial functions of the multivalued logic
- Bounds on Shannon functions of lengths of contact closure tests for contact circuits
- Conditions of A-completeness for linear automata over dyadic rationals
- Learning of monotone functions with single error correction
- Multitype weakly subcritical branching processes in random environment
- Convex algebras of probability distributions induced by finite associative rings