TY  - UNPB
M1  - working_paper
N2  - This paper proposes two proximal Newton-CG methods for convex nonsmooth optimization problems in composite form. The algorithms are based on a a reformulation of the original nonsmooth problem as the unconstrained minimization of a continuously differentiable function, namely the forward-backward envelope (FBE). 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 approximate solution of a linear system of usually small dimension. 
PB  - ArXiv
A1  - Patrinos, Panagiotis
A1  - Stella, Lorenzo
A1  - Bemporad, Alberto
UR  - http://arxiv.org/abs/1402.6655
Y1  - 2014///
TI  - Forward-backward truncated Newton methods for convex composite optimization
AV  - none
EP  - 39
N1  - A preliminary version of this paper [1] was presented at the 52nd IEEE Conference on Decision and Control, Florence, Italy, December 11, 2013.
ID  - eprints2225
ER  -