mlsanityData to 7 Oct 2026

Learning bounded subsets of Lp

arXiv 2002.01182 ↗First posted 4 Feb 2020stat.ML cs.LG math.STcited by 1

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Abstract (arXiv)

We study learning problems in which the underlying class is a bounded subset of Lp and the target Y belongs to Lp. Previously, minimax sample complexity estimates were known under such boundedness assumptions only when p=∞. We present a sharp sample complexity estimate that holds for any p > 4. It is based on a learning procedure that is suited for heavy-tailed problems.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). First posted on arXiv 4 Feb 2020.

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Citing papers per year: 2021: 1.

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  1. 2021Distribution-Free Robust Linear Regressioncited by 19