A vector-contraction inequality for Rademacher complexities

Andreas Maurer

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arXiv · 1605.00251

A vector-contraction inequality for Rademacher complexities

Andreas Maurer

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Abstract

The contraction inequality for Rademacher averages is extended to Lipschitz functions with vector-valued domains, and it is also shown that in the bounding expression the Rademacher variables can be replaced by arbitrary iid symmetric and sub-gaussian variables. Example applications are given for multi-category learning, K-means clustering and learning-to-learn.

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Andreas Maurer. 2016-05-01. A vector-contraction inequality for Rademacher complexities. https://arxiv.org/abs/1605.00251

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