On uniform concentration bounds for Bi-clustering by using the Vapnik–Chervonenkis theory
| Autor: | Saptarshi Chakraborty, Swagatam Das |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Statistics and Probability
010102 general mathematics Strong consistency Bi clustering Row and column spaces 01 natural sciences Data matrix (multivariate statistics) Task (project management) 010104 statistics & probability Vapnik–Chervonenkis theory 0101 mathematics Statistics Probability and Uncertainty Algorithm Mathematics |
| Zdroj: | Statistics & Probability Letters. 175:109102 |
| ISSN: | 0167-7152 |
| DOI: | 10.1016/j.spl.2021.109102 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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