Computational experience with numerical methods for nonnegative least-squares problems

Stefania Bellavia; Jacek Gondzio; Benedetta Morini

doi:10.1002/nla.732

Computational experience with numerical methods for nonnegative least-squares problems

Stefania Bellavia, Jacek Gondzio, Benedetta Morini

School of Mathematics

Research output: Contribution to journal › Article › peer-review

Abstract

We discuss the solution of large-scale box-constrained linear least-squares problems by two recent affine-scaling methods: a cyclic Barzilai-Borwein strategy and an Inexact Newton-like method where a preconditioning technique allows for an efficient computation of the steps. A robust globally and fast locally convergent method based on the combination of the two procedures is presented along with extensive numerical results. Copyright (C) 2010 John Wiley & Sons, Ltd.

Original language	English
Pages (from-to)	363-385
Number of pages	23
Journal	Numerical Linear Algebra with Applications
Volume	18
Issue number	3
DOIs	https://doi.org/10.1002/nla.732
Publication status	Published - May 2011

Keywords / Materials (for Non-textual outputs)

bound-constrained least-squares problems
inexact Newton methods
preconditioning
cyclic Barzilai-Borwein strategy
BOX-CONSTRAINED OPTIMIZATION
BOUNDS
ALGORITHM
SUBJECT
SYSTEMS

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10.1002/nla.732

Computational Experience with Numerical Methods For Nonnegative Least-Squares ProblemsSubmitted manuscript, 745 KB

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title = "Computational experience with numerical methods for nonnegative least-squares problems",

abstract = "We discuss the solution of large-scale box-constrained linear least-squares problems by two recent affine-scaling methods: a cyclic Barzilai-Borwein strategy and an Inexact Newton-like method where a preconditioning technique allows for an efficient computation of the steps. A robust globally and fast locally convergent method based on the combination of the two procedures is presented along with extensive numerical results. Copyright (C) 2010 John Wiley \& Sons, Ltd.",

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AB - We discuss the solution of large-scale box-constrained linear least-squares problems by two recent affine-scaling methods: a cyclic Barzilai-Borwein strategy and an Inexact Newton-like method where a preconditioning technique allows for an efficient computation of the steps. A robust globally and fast locally convergent method based on the combination of the two procedures is presented along with extensive numerical results. Copyright (C) 2010 John Wiley & Sons, Ltd.

KW - bound-constrained least-squares problems

KW - inexact Newton methods

KW - preconditioning

KW - cyclic Barzilai-Borwein strategy

KW - BOX-CONSTRAINED OPTIMIZATION

KW - BOUNDS

KW - ALGORITHM

KW - SUBJECT

KW - SYSTEMS

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ER -

Computational experience with numerical methods for nonnegative least-squares problems

Abstract

Keywords / Materials (for Non-textual outputs)

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