Barrier subgradient method

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.

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Year of publication:	2008-10-01
Authors:	NESTEROV, Y.
Institutions:	Center for Operations Research and Econometrics (CORE), École des Sciences Économiques de Louvain
Subject:	convex optimization \| subgradient methods \| non-smooth optimization \| minimax problems \| saddle points \| variational inequalities \| stochastic optimization \| black-box methods \| lower complexity bounds

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Extent:	application/pdf
Series:	CORE Discussion Papers.
Type of publication:	Book / Working Paper
Notes:	The text is part of a series UNIVERSITE CATHOLIQUE DE LOUVAIN, Center for Operations Research and Econometrics (CORE) Number 2008060
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005065359