Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Benchmarking algorithms of various families #68

Open
GeoffNN opened this issue Jun 18, 2020 · 6 comments
Open

Benchmarking algorithms of various families #68

GeoffNN opened this issue Jun 18, 2020 · 6 comments

Comments

@GeoffNN
Copy link
Collaborator

GeoffNN commented Jun 18, 2020

It would be nice to have an example to compare speed of convergence of SAGA/SVRG/SFW on problems attaining the same optimum.

@GeoffNN
Copy link
Collaborator Author

GeoffNN commented Nov 17, 2020

This can be inspired by the trivial example https://github.com/openopt/chop/blob/master/examples/optim_dynamics.py

@GeoffNN
Copy link
Collaborator Author

GeoffNN commented Nov 19, 2020

It would also be really nice to benchmark algorithms on nonconvex problems. Do the usual practical acceleration methods (backtracking line search) work here?

@fabianp
Copy link
Member

fabianp commented Nov 24, 2020

backtracking does work (in theory and practice) on non-convex problems

@GeoffNN
Copy link
Collaborator Author

GeoffNN commented Nov 25, 2020

I meant does it work for accelerating convergence in practice on non-convex problems?

@fabianp
Copy link
Member

fabianp commented Nov 25, 2020 via email

@fabianp
Copy link
Member

fabianp commented Nov 25, 2020

(as long as we're talking about deterministic algorithms, the top comment makes it confusing)

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Projects
None yet
Development

No branches or pull requests

2 participants