Web: http://arxiv.org/abs/2001.11704

Sept. 23, 2022, 1:12 a.m. | Noga Alon, Alon Gonen, Elad Hazan, Shay Moran

cs.LG updates on arXiv.org arxiv.org

Boosting is a celebrated machine learning approach which is based on the idea
of combining weak and moderately inaccurate hypotheses to a strong and accurate
one. We study boosting under the assumption that the weak hypotheses belong to
a class of bounded capacity. This assumption is inspired by the common
convention that weak hypotheses are "rules-of-thumbs" from an "easy-to-learn
class". (Schapire and Freund~'12, Shalev-Shwartz and Ben-David '14.) Formally,
we assume the class of weak hypotheses has a bounded VC dimension. …

arxiv boosting

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