Estimation of matrices with row sparsity

O. Klopp; A. B. Tsybakov

doi:10.1134/S0032946015040031

Estimation of matrices with row sparsity

O. Klopp
, A. B. Tsybakov

Université Paris-Nanterre
ENSAE

Résultats de recherche: Contribution à un journal › Article › Revue par des pairs

Résumé

An increasing number of applications is concerned with recovering a sparse matrix from noisy observations. In this paper, we consider the setting where each row of an unknown matrix is sparse. We establish minimax optimal rates of convergence for estimating matrices with row sparsity. A major focus in the present paper is on the derivation of lower bounds.

langue originale	Anglais
Pages (de - à)	335-348
Nombre de pages	14
journal	Problems of Information Transmission
Volume	51
Numéro de publication	4
Les DOIs	https://doi.org/10.1134/S0032946015040031
état	Publié - 1 oct. 2015
Modification externe	Oui

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10.1134/S0032946015040031

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title = "Estimation of matrices with row sparsity",

abstract = "An increasing number of applications is concerned with recovering a sparse matrix from noisy observations. In this paper, we consider the setting where each row of an unknown matrix is sparse. We establish minimax optimal rates of convergence for estimating matrices with row sparsity. A major focus in the present paper is on the derivation of lower bounds.",

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AB - An increasing number of applications is concerned with recovering a sparse matrix from noisy observations. In this paper, we consider the setting where each row of an unknown matrix is sparse. We establish minimax optimal rates of convergence for estimating matrices with row sparsity. A major focus in the present paper is on the derivation of lower bounds.

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Estimation of matrices with row sparsity

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