Greedy Strategies for Convex Optimization

被引：10

作者：

Hao Nguyen ^{[1
]}

Petrova, Guergana ^{[2
]}

机构：

[1] WorldQuant LLC, Hanoi, Vietnam

[2] Texas A&M Univ, Dept Math, College Stn, TX 77843 USA

来源：

CALCOLO | 2017年 / 54卷 / 01期

基金：

美国国家科学基金会;

关键词：

Greedy algorithms; Convex optimization; Rates of convergence; APPROXIMATION;

D O I：

10.1007/s10092-016-0183-2

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

We investigate two greedy strategies for finding an approximation to the minimum of a convex function E defined on a Hilbert space H. We prove convergence rates for these algorithms under suitable conditions on the objective function E. These conditions involve the behavior of the modulus of smoothness and the modulus of uniform convexity of E.

引用

页码：207 / 224

页数：18

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