This organization regroups works/packages/toolboxes related to performance estimation problems.
If you find some content useful, please don't hesitate to give feedbacks and or to star the content!
- PESTO: allows a quick access to performance estimation problems in Matlab.
- PEPit: allows a quick access to performance estimation problems in Python.
There are also related works on using performance estimation problems for finding Lyapunov (or potential, or energy) functions. Those techniques were not included in PESTO and PEPit yet (for structural reasons), which currently only allow to study pre-defined Lyapunov functions (as opposed to find them). Two of those works provide easy-to-use interfaces:
- Lyapunov functions for linear convergence of first-order methods for smooth strongly convex problems (in Matlab),
- Lyapunov functions for splitting methods (in Python).
If you organize a PEP-event, we would be happy to list your event below.
Past events:
- February 2023: PEP-talks.
If you have any feedback or other input, please don't hesitate to contribute by sharing it. We are happy to review any constructive pull request. In particular, if you find any example of application that you find relevant, don't hesitate to submit it as a new example within one of the toolboxes and/or to the learning performance estimation problems repository.