Limited-memory BFGS
id:
limited-memory-bfgs-293-14509158
title:
Limited-memory BFGS
text:
Limited-memory BFGS (L-BFGS or LM-BFGS) is an optimization algorithm in the family of quasi-Newton methods that approximates the Broyden–Fletcher–Goldfarb–Shanno algorithm (BFGS) using a limited amount of computer memory. It is a popular algorithm for parameter estimation in machine learning. The algorithm's target problem is to minimize f ( x ) over unconstrained values of the real-vector x where f is a differentiable scalar function. Like the original BFGS, L-BFGS uses an estimate of the inver
brand slug:
wiki
category slug:
encyclopedia
description:
Optimization algorithm
original url:
https://en.wikipedia.org/wiki/Limited-memory_BFGS
date created:
date modified:
2023-12-28T06:13:42Z
main entity:
{"identifier":"Q6549489","url":"https://www.wikidata.org/entity/Q6549489"}
image:
fields total:
13
integrity:
14