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Forward-backward truncated Newton methods for convex composite optimization

2014/02/26 by Patrinos, Panagiotis, Stella, Lorenzo, Bemporad, Alberto
#FOS: Mathematics #Optimization and Control (math.OC)

paper · doi:10.48550/arxiv.1402.6655

Abstract

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.

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