On uniform concentration bounds for Bi-clustering by using the Vapnik–Chervonenkis theory

Saptarshi Chakraborty and Swagatam Das

Statistics & Probability Letters, 2021, vol. 175, issue C

Abstract: Bi-clustering refers to the task of partitioning the rows and columns of a data matrix simultaneously. Although empirically useful, the theoretical aspects of bi-clustering techniques have not been studied in-depth. We present a framework for investigating the statistical guarantees behind the sparse bi-clustering algorithm by using the Vapnik–Chervonenkis (VC) theory.

Keywords: Bi-clustering; VC theory; Strong consistency (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1016/j.spl.2021.109102

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