Proximal gradient method
id:
proximal-gradient-method-307-16372265
title:
Proximal gradient method
text:
Proximal gradient methods are a generalized form of projection used to solve non-differentiable convex optimization problems. Many interesting problems can be formulated as convex optimization problems of the form min x ∈ R N ∑ i = 1 n f i where f i : R N → R , i = 1 , … , n are possibly non-differentiable convex functions. The lack of differentiability rules out conventional smooth optimization techniques like the steepest descent method and the conjugate gradient method, but proximal gradi
brand slug:
wiki
category slug:
encyclopedia
description:
original url:
https://en.wikipedia.org/wiki/Proximal_gradient_method
date created:
date modified:
2023-12-06T15:46:49Z
main entity:
{"identifier":"Q17086765","url":"https://www.wikidata.org/entity/Q17086765"}
image:
{"content_url":"https://upload.wikimedia.org/wikipedia/commons/7/70/Frank_Wolfe_vs_Projected_Gradient.webm","width":1280,"height":720}
fields total:
13
integrity:
14