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.
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|
|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|
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