Sample compression, learnability, and the Vapnik-Chervonenkis dimension
نویسندگان
چکیده
منابع مشابه
Vapnik-chervonenkis Dimension 1 Vapnik-chervonenkis Dimension
Valiant’s theorem from the previous lecture is meaningless for infinite hypothesis classes, or even classes with more than exponential size. In 1968, Vladimir Vapnik and Alexey Chervonenkis wrote a very original and influential paper (in Russian) [5, 6] which allows us to estimate the sample complexity for infinite hypothesis classes too. The idea is that the size of the hypothesis class is a p...
متن کاملResults on Learnability and the Vapnik-Chervonenkis Dimension*
We consider the problem of learning a concept from examples in the distributionfree model by Valiant. (An essentially equivalent model, if one ignores issues of computational difficulty, was studied by Vapnik and Chervonenkis.) We introduce the notion of dynamic sampling, wherein the number of examples examined may increase with the complexity of the target concept. This method is used to estab...
متن کاملResults on learnability and the Vapnik-Chervonenkis dimension (Extended Abstract)
We consider the problem of learning a concept from examples in the distributionfree model by Valiant. (An essentially equivalent model, if one ignores issues of computational difficulty, was studied by Vapnik and Chervonenkis.) We introduce the notion of dynamic sampling, wherein the number of examples examined may increase with the complexity of the target concept. This method is used to estab...
متن کاملBounding Sample Size with the Vapnik-Chervonenkis Dimension
A proof that a concept 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 4log2(e).
متن کاملVapnik-Chervonenkis Dimension and (Pseudo-)Hyperplane Arrangements
An arrangement of oriented pseudohyperplanes in affine d-space defines on its set X of pseudohyperplanes a set system (or range space) (X,R), R ⊆ 2 of VCdimension d in a natural way: to every cell c in the arrangement assign the subset of pseudohyperplanes having c on their positive side, and let R be the collection of all these subsets. We investigate and characterize the range spaces correspo...
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ژورنال
عنوان ژورنال: Machine Learning
سال: 1995
ISSN: 0885-6125,1573-0565
DOI: 10.1007/bf00993593