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@PerformanceEstimation

PerformanceEstimation

README.md

PerformanceEstimation

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!

Current packages

  • 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:

Education

  • Informal introduction to PEPs: here.
  • Practical exercises: here.

Events

If you organize a PEP-event, we would be happy to list your event below.

Past events:

Contributing

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.

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  1. Performance-Estimation-Toolbox Performance-Estimation-Toolbox Public

    Code of the Performance Estimation Toolbox (PESTO) whose aim is to ease the access to the PEP methodology for performing worst-case analyses of first-order methods in convex and nonconvex optimizat…

    MATLAB 52 6

  2. PEPit PEPit Public

    PEPit is a package enabling computer-assisted worst-case analyses of first-order optimization methods.

    Python 82 13

  3. Learning-Performance-Estimation Learning-Performance-Estimation Public

    This repository regroups learning ressources about performance estimation problems

    Jupyter Notebook 12 2

Repositories

Showing 6 of 6 repositories
  • PEPit Public

    PEPit is a package enabling computer-assisted worst-case analyses of first-order optimization methods.

    PerformanceEstimation/PEPit’s past year of commit activity
    Python 82 MIT 13 2 4 Updated Oct 9, 2024
  • Learning-Performance-Estimation Public

    This repository regroups learning ressources about performance estimation problems

    PerformanceEstimation/Learning-Performance-Estimation’s past year of commit activity
    Jupyter Notebook 12 MIT 2 0 0 Updated Sep 19, 2024
  • Performance-Estimation-Toolbox Public

    Code of the Performance Estimation Toolbox (PESTO) whose aim is to ease the access to the PEP methodology for performing worst-case analyses of first-order methods in convex and nonconvex optimization. The numerical worst-case analyses from PEP can be performed just by writting the algorithms just as you would implement them.

    PerformanceEstimation/Performance-Estimation-Toolbox’s past year of commit activity
    MATLAB 52 MIT 6 0 0 Updated Feb 20, 2024
  • .github Public
    PerformanceEstimation/.github’s past year of commit activity
    0 1 0 0 Updated Feb 27, 2023
  • PEP-talks Public
    PerformanceEstimation/PEP-talks’s past year of commit activity
    HTML 0 GPL-3.0 0 0 0 Updated Feb 23, 2023
  • performanceestimation.github.io Public
    PerformanceEstimation/performanceestimation.github.io’s past year of commit activity
    0 0 0 0 Updated Oct 4, 2022

People

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