Hyperfast second-order local solvers for efficient statistically preconditioned distributed optimization

Statistical preconditioning enables fast methods for distributed large-scale empirical risk minimization problems. In this approach, multiple worker nodes compute gradients in parallel, which are then used by the central node to update the parameter by solving an auxiliary (preconditioned) smaller-s...

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Bibliographic Details

Published in:	EURO journal on computational optimization Vol. 10; p. 100045
Main Authors:	Dvurechensky, Pavel, Kamzolov, Dmitry, Lukashevich, Aleksandr, Lee, Soomin, Ordentlich, Erik, Uribe, César A., Gasnikov, Alexander
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 2022 Elsevier
Subjects:	Distributed optimization Empirical risk minimization Statistical preconditioning Tensor optimization methods Empirical risk minimization Distributed optimization Tensor optimization methods Statistical preconditioning
ISSN:	2192-4406
Online Access:	Get full text
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