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A randomized method for smooth convex minimization, motivated by probability maximization

Csaba I Fabian (fabian.csaba***at***gamf.kefo.hu)
Tamas Szantai (szantai***at***math.bme.hu)

Abstract: We propose a randomized gradient method - or a randomized cutting-plane method from a dual viewpoint. From the primal viewpoint, our method bears a resemblance to the stochastic approximation family. But in contrast to stochastic approximation, the present method builds a model problem.

Keywords: Convex optimization, stochastic optimization, probabilistic problems

Category 1: Stochastic Programming

Category 2: Nonlinear Optimization

Citation: Kecskemet College, Pallasz Athene University. Izsaki ut 10, 6000 Kecskemet, Hungary; and Budapest University of Technology and Economics. Muegyetem rkp 3-9, 1111 Budapest, Hungary.

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Entry Submitted: 03/24/2017
Entry Accepted: 03/24/2017
Entry Last Modified: 03/26/2017

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