This jupyter notebook contains an implementation of the paper "Two efficient gradient methods with approximately optimal stepsizes based on regularization models for unconstrained optimization", by Zexian Liu, Wangli Chu, Hongwei Liu.
-
Notifications
You must be signed in to change notification settings - Fork 0
This jupyter notebook contains an implementation of the paper "Two efficient gradient methods with approximately optimal stepsizes based on regularization models for unconstrained optimization".
ErnestoR2/Efficient_Gradient_Methods
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
Folders and files
Name | Name | Last commit message | Last commit date | |
---|---|---|---|---|
Repository files navigation
About
This jupyter notebook contains an implementation of the paper "Two efficient gradient methods with approximately optimal stepsizes based on regularization models for unconstrained optimization".
Resources
Stars
Watchers
Forks
Releases
No releases published
Packages 0
No packages published