AbstractA proof that a concept class is learnable provided the Vapnik—Chervonenkis dimension is finite is given. The proof is more explicit than previous proofs and introduces two new parameters which allow bounds on the sample size obtained to be improved by a factor of approximately 4 log2(e)
We prove alower bound of ( 1 ln 1 + VCdim(C) ) on the number of random examples required for distrib...
AbstractValiant's protocol for learning is extended to the case where the distribution of the exampl...
The Vapnik-Chervonenkis (VC) dimension is a combinatorial measure of a certain class of machine lear...
A proof that a concept is learnable provided the Vapnik-Chervonenkis dimension is finite is given. T...
AbstractA proof that a concept class is learnable provided the Vapnik—Chervonenkis dimension is fini...
A proof that a concept class is learnable provided the Vapnik—Chervonenkis dimension is finite is gi...
We consider the problem of learning a concept from examples in the distribution-free model by Valian...
AbstractWe consider the problem of learning a concept from examples in the distribution-free model b...
Abstract. The Vapnik-Chervonenkis (V-C) dimension is an important combinatorial tool in the analysis...
AbstractN. Linialet al.raised the question of how difficult the computation of the Vapnik–Červonenki...
Abstract. Within the framework of pac-learning, we explore the learnability of concepts from samples...
AbstractWe prove a lower bound of Ω((1/ɛ)ln(1/δ)+VCdim(C)/ɛ) on the number of random examples requir...
Lecture Notes in Artificial Intelligence 744, 279-287, 1993The Vapnik-Chervonenkis (VC) dimension is...
. Within the framework of pac-learning, we explore the learnability of concepts from samples using t...
Within the framework of pac-learning, we explore the learnability of concepts from samples using the...
We prove alower bound of ( 1 ln 1 + VCdim(C) ) on the number of random examples required for distrib...
AbstractValiant's protocol for learning is extended to the case where the distribution of the exampl...
The Vapnik-Chervonenkis (VC) dimension is a combinatorial measure of a certain class of machine lear...
A proof that a concept is learnable provided the Vapnik-Chervonenkis dimension is finite is given. T...
AbstractA proof that a concept class is learnable provided the Vapnik—Chervonenkis dimension is fini...
A proof that a concept class is learnable provided the Vapnik—Chervonenkis dimension is finite is gi...
We consider the problem of learning a concept from examples in the distribution-free model by Valian...
AbstractWe consider the problem of learning a concept from examples in the distribution-free model b...
Abstract. The Vapnik-Chervonenkis (V-C) dimension is an important combinatorial tool in the analysis...
AbstractN. Linialet al.raised the question of how difficult the computation of the Vapnik–Červonenki...
Abstract. Within the framework of pac-learning, we explore the learnability of concepts from samples...
AbstractWe prove a lower bound of Ω((1/ɛ)ln(1/δ)+VCdim(C)/ɛ) on the number of random examples requir...
Lecture Notes in Artificial Intelligence 744, 279-287, 1993The Vapnik-Chervonenkis (VC) dimension is...
. Within the framework of pac-learning, we explore the learnability of concepts from samples using t...
Within the framework of pac-learning, we explore the learnability of concepts from samples using the...
We prove alower bound of ( 1 ln 1 + VCdim(C) ) on the number of random examples required for distrib...
AbstractValiant's protocol for learning is extended to the case where the distribution of the exampl...
The Vapnik-Chervonenkis (VC) dimension is a combinatorial measure of a certain class of machine lear...
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