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arxiv: 1605.00251 · v1 · pith:XDT7HNKQnew · submitted 2016-05-01 · 💻 cs.LG · stat.ML

A vector-contraction inequality for Rademacher complexities

Andreas Maurer This is my paper
classification 💻 cs.LG stat.ML
keywords rademacherinequalityvariablesapplicationsarbitraryaveragesboundingclustering
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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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