@unpublished{eprints2225,
           title = {Forward-backward truncated Newton methods for convex composite optimization},
            note = {A preliminary version of this paper [1] was presented at the 52nd IEEE Conference on Decision and Control, Florence, Italy, December 11, 2013.},
            type = {Working Paper},
       publisher = {ArXiv},
            year = {2014},
     institution = {IMT Institute for Advanced Studies Lucca},
          author = {Panagiotis Patrinos and Lorenzo Stella and Alberto Bemporad},
        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. },
             url = {http://eprints.imtlucca.it/2225/}
}