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)
Full text not available from this repository.Abstract
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: | https://doi.org/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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