mlsanityData to 14 Oct 2026

A Chain Rule for the Expected Suprema of Bernoulli Processes

arXiv 2304.14474 ↗First posted 27 Apr 2023math.PR cs.LG stat.MLcited by 1

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Abstract (arXiv)

We obtain an upper bound on the expected supremum of a Bernoulli process indexed by the image of an index set under a uniformly Lipschitz function class in terms of properties of the index set and the function class, extending an earlier result of Maurer for Gaussian processes. The proof makes essential use of recent results of Bednorz and Latala on the boundedness of Bernoulli processes.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 3 of its 8 references that are in the map. First posted on arXiv 27 Apr 2023.

Builds on

3 of 8 references.

References · 3

  1. 2017Size-Independent Sample Complexity of Neural Networkscited by 290
  2. 2016A vector-contraction inequality for Rademacher complexitiescited by 142
  3. 2014A chain rule for the expected suprema of Gaussian processescited by 13

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Citing papers per year: 2024: 1.

1 paper.

  1. 2024On Generalization Bounds for Neural Networks with Low Rank Layerscited by 4