Barrier subgradient method

Y. Nesterov
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Y. Nesterov: Université catholique de Louvain (UCL). Center for Operations Research and Econometrics (CORE)

No 2008060, LIDAM Discussion Papers CORE from Université catholique de Louvain, Center for Operations Research and Econometrics (CORE)

Abstract: In this paper we develop a new primal-dual subgradient method for nonsmooth convex optimization problems. This scheme is based on a self-concordant barrier for the basic feasible set. It is suitable for finding approximate solutions with certain relative accuracy. We discuss some applications of this technique including fractional covering problem, maximal concurrent flow problem, semidefinite relaxations and nonlinear online optimization.

Keywords: convex optimization; subgradient methods; non-smooth optimization; minimax problems; saddle points; variational inequalities; stochastic optimization; black-box methods; lower complexity bounds. (search for similar items in EconPapers)
Date: 2008-10-01
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Persistent link: https://EconPapers.repec.org/RePEc:cor:louvco:2008060

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