Add to ORKGWe demonstrate that the Vapnik-Chervonenkis dimension of the class of monotone formulas over n variables is exactly � n ⌊n/2
Vapnik Chervonenkis dimension is a basic combinatorial notion with applications in machine learnin...
We prove a hierarchy theorem for the representation of monotone Boolean functions by monotone Boolea...
The Vapnik-Chervonenkis (VC) dimension (also known as the trace number) and the Sauer-Shelah lemma ...
We show that the Vapnik-Chervonenkis dimension of Boolean monomials over n variables is at most n fo...
AbstractN. Linialet al.raised the question of how difficult the computation of the Vapnik–Červonenki...
AbstractIn the PAC-learning model, the Vapnik-Chervonenkis (VC) dimension plays the key role to esti...
The Vapnik-Chervonenkis (VC) dimension is used to measure the complexity of a function class and pla...
Proc. European Conference on Machine Learning, Lecture Notes in Artificial Intelligence 784, 415-418...
In the PAC-learning model, the Vapnik-Chervonenkis (VC) dimension plays the key role to estimate the...
Lecture Notes in Artificial Intelligence 744, 279-287, 1993The Vapnik-Chervonenkis (VC) dimension is...
ABSTRACT: We prove a hierarchy theorem for the representation of monotone Boolean functions by monot...
Abstract. The Vapnik-Chervonenkis (V-C) dimension is an important combinatorial tool in the analysis...
The Vapnik-Chervonenkis (VC) dimension of the set of half-spaces of Rd with frontiers parallel to th...
Abstract. The Vapnik-Chervonenkis (VC) dimension plays an important role in statistical learning the...
A proof that a concept is learnable provided the Vapnik-Chervonenkis dimension is finite is given. T...
Vapnik Chervonenkis dimension is a basic combinatorial notion with applications in machine learnin...
We prove a hierarchy theorem for the representation of monotone Boolean functions by monotone Boolea...
The Vapnik-Chervonenkis (VC) dimension (also known as the trace number) and the Sauer-Shelah lemma ...
We show that the Vapnik-Chervonenkis dimension of Boolean monomials over n variables is at most n fo...
AbstractN. Linialet al.raised the question of how difficult the computation of the Vapnik–Červonenki...
AbstractIn the PAC-learning model, the Vapnik-Chervonenkis (VC) dimension plays the key role to esti...
The Vapnik-Chervonenkis (VC) dimension is used to measure the complexity of a function class and pla...
Proc. European Conference on Machine Learning, Lecture Notes in Artificial Intelligence 784, 415-418...
In the PAC-learning model, the Vapnik-Chervonenkis (VC) dimension plays the key role to estimate the...
Lecture Notes in Artificial Intelligence 744, 279-287, 1993The Vapnik-Chervonenkis (VC) dimension is...
ABSTRACT: We prove a hierarchy theorem for the representation of monotone Boolean functions by monot...
Abstract. The Vapnik-Chervonenkis (V-C) dimension is an important combinatorial tool in the analysis...
The Vapnik-Chervonenkis (VC) dimension of the set of half-spaces of Rd with frontiers parallel to th...
Abstract. The Vapnik-Chervonenkis (VC) dimension plays an important role in statistical learning the...
A proof that a concept is learnable provided the Vapnik-Chervonenkis dimension is finite is given. T...
Vapnik Chervonenkis dimension is a basic combinatorial notion with applications in machine learnin...
We prove a hierarchy theorem for the representation of monotone Boolean functions by monotone Boolea...
The Vapnik-Chervonenkis (VC) dimension (also known as the trace number) and the Sauer-Shelah lemma ...