2014/12/12 by Alexander Gasnikov, Gasnikov, Alexander, Anastasia Lagunovskaya +5
Computer Science · Engineering · Mathematics · #Advanced Optimization Algorithms Research #FOS: Mathematics #Optimization and Control (math.OC) #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques #math.OC
paper · pdf · doi:10.48550/arxiv.1412.3890
26 pages, in Russian, Avtomatika i Telemekhanika. 2016
openalex publication_date 2014/12/12 · arxiv created 2016/04/17 · arxiv updated 2016/04/19 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
In the paper we show that euclidian randomization in some situations (i.e. for gradient-free method on a simplex) can be as good as the randomization on the unit sphere in 1-norm. That is on the simplex example we show that for gradient-free methods the choise of the prox-structure and the choise of a way of randomization have to be connected to each other. We demonstrate how it can be done in an optimal way. It is important that we consider inexact oracle.