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Fast Detection of Block Boundaries in Block-Wise Constant Matrices

Perner, Petra

Lecture Notes in Computer Science, 2016, Vol.9729, p.214-228 [Periódico revisado por pares]

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Título:
Fast Detection of Block Boundaries in Block-Wise Constant Matrices
Autor: Perner, Petra
Assuntos: Artificial intelligence ; Change-points ; HiC experiments ; High-dimensional sparse linear model ; Mathematics ; Statistics
É parte de: Lecture Notes in Computer Science, 2016, Vol.9729, p.214-228
Descrição: We propose a novel approach for estimating the location of block boundaries (change-points) in a random matrix consisting of a block wise constant matrix observed in white noise. Our method consists in rephrasing this task as a variable selection issue. We use a penalized least-squares criterion with an \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document} ell _1 end{document}-type penalty for dealing with this problem. We first provide some theoretical results ensuring the consistency of our change-point estimators. Then, we explain how to implement our method in a very efficient way. Finally, we provide some empirical evidence to support our claims and apply our approach to data coming from molecular biology which can be used for better understanding the structure of the chromatin.
Títulos relacionados: Lecture Notes in Computer Science
Editor: Switzerland: Springer International Publishing AG
Idioma: Inglês

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