TY  - CHAP
T2  - 52nd IEEE Conference on Decision and Control
EP  - 2363
ID  - eprints2226
SP  - 2358
N2  - 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.
A1  - Patrinos, Panagiotis
A1  - Bemporad, Alberto
PB  - IEEE
SN  - 978-1-4673-5714-2 
UR  - http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6760233&isnumber=6759837
AV  - none
TI  - Proximal Newton methods for convex composite optimization
Y1  - 2013/12//
KW  - Approximation algorithms
KW  -  Approximation methods
KW  -  Convergence
KW  -  Gradient methods
KW  -  Radio frequency
KW  -  Signal processing algorithms
ER  -