Ramsey theory (2nd ed.)
Identification of unions of languages drawn from an identifiable class
COLT '89 Proceedings of the second annual workshop on Computational learning theory
The correct definition of finite elasticity: corrigendum to identification of unions
COLT '91 Proceedings of the fourth annual workshop on Computational learning theory
SIAM Journal on Computing
Learning algebraic structures from text
Theoretical Computer Science - Algorithmic learning theory
Algebraic Theory of Automata & Languages
Algebraic Theory of Automata & Languages
A non-learnable class of E-pattern languages
Theoretical Computer Science - Algorithmic learning theory(ALT 2002)
Set systems: Order types, continuous nondeterministic deformations, and quasi-orders
Theoretical Computer Science
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To develop computational learning theory of commutative regular shuffle closed languages, we study finite elasticity for classes of (semi)group-like structures. One is the class of A *** d + F such that A is a matrix of size e ×d with nonnegative integer entries and F consists of at most k number of e -dimensional nonnegative integer vectors, and another is the class $\mathcal{X}^{d}_{k}$ of A *** d + F such that A is a square matrix of size d with integer entries and F consists of at most k number of d -dimensional integer vectors (F is repeated according to the lattice A *** d ). Each class turns out to be the elementwise unions of k -copies of a more manageable class. So we formulate "learning time" of a class and then study in general setting how much "learning time" is increased by the elementwise union, by using Ramsey number. We also point out that such a standpoint can be generalized by using Noetherian spaces.