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Improved algorithms for convex minimization in relative scale

Peter Richtarik(peter.richtarik***at***uclouvain.be)

Abstract: In this paper we propose two modifications to Nesterov's algorithms for minimizing convex functions in relative scale. The first is based on a bisection technique and leads to improved theoretical iteration complexity, and the second is a heuristic for avoiding restarting behavior. The fastest of our algorithms produces a solution within relative error O(1/k) of the optimum, with k being the iteration counter.

Keywords: convex optimization, relative scale, sublinearity, Nesterov's smoothing technique, Lowner-John ellipsoids

Category 1: Convex and Nonsmooth Optimization (Convex Optimization )

Citation:

Download: [PDF]

Entry Submitted: 02/09/2009
Entry Accepted: 02/09/2009
Entry Last Modified: 02/09/2009

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