AbstractWe define embeddings between concept classes that are meant to reflect certain aspects of their combinatorial structure. Furthermore, we introduce a notion of universal concept classes - classes into which any member of a given family of classes can be embedded. These universal classes play a role similar to that played in computational complexity by languages that are hard for a given complexity class. We show that classes of half-spaces in Rn are universal with respect to families of algebraically defined classes.We present some combinatorial parameters along which the family of classes of a given VC-dimension can be grouped into sub-families. We use these parameters to investigate the existence of embeddings and the scope of univ...
We examine connections between combinatorial notions that arise in machine learning and topological ...
In 1998, it was proved by Ben-David and Litman that a concept space has a sample compression scheme ...
AbstractA proof that a concept class is learnable provided the Vapnik—Chervonenkis dimension is fini...
AbstractWe define embeddings between concept classes that are meant to reflect certain aspects of th...
Abstract. Within the framework of pac-learning, we explore the learnability of concepts from samples...
Within the framework of pac-learning, we explore the learnability of concepts from samples using the...
. Within the framework of pac-learning, we explore the learnability of concepts from samples using t...
This paper presents a construction of a proper and stable labelled sample compression scheme of size...
Abstract. Sample compression schemes are schemes for “encoding ” a set of examples in a small subset...
Any set of labeled examples consistent with some hidden orthogonal rectan-gle can be \compressed &qu...
Maximum concept classes of VC dimension d over n domain points have size � n � ≤d, and this is an up...
AbstractWe consider the problem of learning a concept from examples in the distribution-free model b...
We consider the problem of learning a concept from examples in the distribution-free model by Valian...
Any set of labeled examples consistent with some hidden orthogonal rectan-gle can be “compressed ” t...
It was proved by Ben-David and Litman that a concept space with VC dimension d has a sample compress...
We examine connections between combinatorial notions that arise in machine learning and topological ...
In 1998, it was proved by Ben-David and Litman that a concept space has a sample compression scheme ...
AbstractA proof that a concept class is learnable provided the Vapnik—Chervonenkis dimension is fini...
AbstractWe define embeddings between concept classes that are meant to reflect certain aspects of th...
Abstract. Within the framework of pac-learning, we explore the learnability of concepts from samples...
Within the framework of pac-learning, we explore the learnability of concepts from samples using the...
. Within the framework of pac-learning, we explore the learnability of concepts from samples using t...
This paper presents a construction of a proper and stable labelled sample compression scheme of size...
Abstract. Sample compression schemes are schemes for “encoding ” a set of examples in a small subset...
Any set of labeled examples consistent with some hidden orthogonal rectan-gle can be \compressed &qu...
Maximum concept classes of VC dimension d over n domain points have size � n � ≤d, and this is an up...
AbstractWe consider the problem of learning a concept from examples in the distribution-free model b...
We consider the problem of learning a concept from examples in the distribution-free model by Valian...
Any set of labeled examples consistent with some hidden orthogonal rectan-gle can be “compressed ” t...
It was proved by Ben-David and Litman that a concept space with VC dimension d has a sample compress...
We examine connections between combinatorial notions that arise in machine learning and topological ...
In 1998, it was proved by Ben-David and Litman that a concept space has a sample compression scheme ...
AbstractA proof that a concept class is learnable provided the Vapnik—Chervonenkis dimension is fini...