西华师范大学学报(自然科学版)2025,Vol.46Issue(1) :30-35.DOI:10.16246/j.issn.1673-5072.2025.01.004

一类非凸Bregman梯度法的线性收敛研究

Linear Convergence of a Class of Non-convex Bregman Gradient Algorithm

李蝶 郭科
西华师范大学学报(自然科学版)2025,Vol.46Issue(1) :30-35.DOI:10.16246/j.issn.1673-5072.2025.01.004

一类非凸Bregman梯度法的线性收敛研究

Linear Convergence of a Class of Non-convex Bregman Gradient Algorithm

李蝶 1郭科1
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作者信息

  • 1. 西华师范大学数学与信息学院,四川南充 637009
  • 折叠

摘要

梯度下降算法是一类求解无约束优化问题的重要方法,其研究中光滑性的假设具有重要作用.Bregman梯度下降算法是对梯度下降算法的一种推广,本质上可以看作将经典的光滑性削弱成相对光滑性时自然产生的.文章研究了 Bregman梯度下降算法求解相对强quasar-凸和相对光滑问题的线性收敛性,证明了当目标函数为相对强quasar-凸且相对光滑时,Bregman梯度下降算法产生的函数值序列具有线性收敛速度,同时,给出了迭代序列的收敛性.

Abstract

Gradient descent algorithm is an important method for solving unconstrained optimization prob-lems,and the assumption of smoothness plays a crucial role in its research.Bregman gradient descent al-gorithm is an extension of the gradient descent algorithm,and it can be essentially seen as a natural out-growth when the classical smoothness is reduced to relative smoothness.This paper studies the linear con-vergence of Bregman gradient descent algorithm for solving relatively strongly quasar-convex and relatively smooth problems.It is proved that when the objective function is relatively strongly quasar-convex and rel-atively smooth,the sequence of function value produced by Bregman gradient descent algorithm has a line-ar convergence rate.Meanwhile,the convergence of iterative sequence is also given.

关键词

相对光滑/强quasar-凸/相对强quasar-凸/Bregman梯度下降算法/线性收敛率

Key words

relatively smooth/strongly quasar-convex/relatively strongly quasar-convex/Bregman gradient descent algorithm/linear convergence rate

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出版年

2025
西华师范大学学报(自然科学版)
西华师范大学

西华师范大学学报(自然科学版)

影响因子:0.212
ISSN:1673-5072
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