Any set of labeled examples consistent with some hidden orthogonal rectan-gle can be \compressed " to at most four examples: An upmost, a leftmost, a rightmost and a bottommost positive example. These four examples represent an orthogonal rectangle (the smallest such rectangle that contains them) that is consistent with all examples. Note that the VC dimension of orthogonal rectangles is four and this is exactly the number of examples needed to represent the consistent orthogonal rectangle. A compression scheme of size k for a concept class C picks from any set of examples consistent with some concept in C a subset of up to k examples and this subset represents (via a mapping that that is speci¯c to the class C) a hypothesis consistent...
In 1998, it was proved by Ben-David and Litman that a concept space has a sample compression scheme ...
AbstractWe define embeddings between concept classes that are meant to reflect certain aspects of th...
International audienceWe examine connections between combinatorial notions that arise in machine lea...
Any set of labeled examples consistent with some hidden orthogonal rectan-gle can be “compressed ” t...
This paper presents a construction of a proper and stable labelled sample compression scheme of size...
Maximum concept classes of VC dimension d over n domain points have size � n � ≤d, and this is an up...
Within the framework of pac-learning, we explore the learnability of concepts from samples using the...
Abstract. Within the framework of pac-learning, we explore the learnability of concepts from samples...
Abstract. Sample compression schemes are schemes for “encoding ” a set of examples in a small subset...
Abstract. We give a compression scheme for any maximum class of VC dimension d that compresses any s...
Abstract. We give a compression scheme for any maximum class of VC dimension d that compresses any s...
One of the earliest conjectures in computational learning theory-the Sample Compression conjecture-a...
It was proved by Ben-David and Litman that a concept space with VC dimension d has a sample compress...
. Within the framework of pac-learning, we explore the learnability of concepts from samples using t...
We show that the topes of a complex of oriented matroids (abbreviated COM) of VC-dimension $d$ admit...
In 1998, it was proved by Ben-David and Litman that a concept space has a sample compression scheme ...
AbstractWe define embeddings between concept classes that are meant to reflect certain aspects of th...
International audienceWe examine connections between combinatorial notions that arise in machine lea...
Any set of labeled examples consistent with some hidden orthogonal rectan-gle can be “compressed ” t...
This paper presents a construction of a proper and stable labelled sample compression scheme of size...
Maximum concept classes of VC dimension d over n domain points have size � n � ≤d, and this is an up...
Within the framework of pac-learning, we explore the learnability of concepts from samples using the...
Abstract. Within the framework of pac-learning, we explore the learnability of concepts from samples...
Abstract. Sample compression schemes are schemes for “encoding ” a set of examples in a small subset...
Abstract. We give a compression scheme for any maximum class of VC dimension d that compresses any s...
Abstract. We give a compression scheme for any maximum class of VC dimension d that compresses any s...
One of the earliest conjectures in computational learning theory-the Sample Compression conjecture-a...
It was proved by Ben-David and Litman that a concept space with VC dimension d has a sample compress...
. Within the framework of pac-learning, we explore the learnability of concepts from samples using t...
We show that the topes of a complex of oriented matroids (abbreviated COM) of VC-dimension $d$ admit...
In 1998, it was proved by Ben-David and Litman that a concept space has a sample compression scheme ...
AbstractWe define embeddings between concept classes that are meant to reflect certain aspects of th...
International audienceWe examine connections between combinatorial notions that arise in machine lea...