Minimizing functions with bounded variation of subgradients

Yu. Nesterov

No 2005079, LIDAM Discussion Papers CORE from Université catholique de Louvain, Center for Operations Research and Econometrics (CORE)

Abstract: In many applications it is possible to justify a reasonable bound for possible variation of subgradients of objective function rather than for their uniform magnitude. In this paper we develop a new class of efficient primal-dual subgradient schemes for such problem classes.

Keywords: convex optimization; subgradient methods; non-smooth optimization; blackbox methods; lower complexity bounds (search for similar items in EconPapers)
Date: 2005-11
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