relation: http://eprints.imtlucca.it/2226/
title: Proximal Newton methods for convex composite optimization
creator: Patrinos, Panagiotis
creator: Bemporad, Alberto
subject: QA75 Electronic computers. Computer science
description: 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.
publisher: IEEE
date: 2013-12
type: Book Section
type: PeerReviewed
identifier:   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)  
relation: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6760233&isnumber=6759837
relation: 10.1109/CDC.2013.6760233