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Proximal Newton methods for convex composite optimization

Patrinos, Panagiotis and Bemporad, Alberto Proximal Newton methods for convex composite optimization. In: 52nd IEEE Conference on Decision and Control. IEEE, pp. 2358-2363. ISBN 978-1-4673-5714-2 (2013)

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This paper proposes two proximal Newton methods for convex nonsmooth optimization problems in composite form. The algorithms are based on a new continuously differentiable exact penalty function, namely the Composite Moreau Envelope. The first algorithm is based on a standard line search strategy, whereas the second one combines the global efficiency estimates of the corresponding first-order methods, while achieving fast asymptotic convergence rates. Furthermore, they are computationally attractive since each Newton iteration requires the solution of a linear system of usually small dimension.

Item Type: Book Section
Identification Number: 10.1109/CDC.2013.6760233
Uncontrolled Keywords: Approximation algorithms, Approximation methods, Convergence, Gradient methods, Radio frequency, Signal processing algorithms
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Research Area: Computer Science and Applications
Depositing User: Ms T. Iannizzi
Date Deposited: 01 Jul 2014 11:13
Last Modified: 01 Jul 2014 11:13
URI: http://eprints.imtlucca.it/id/eprint/2226

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