GitHub topics: performance-estimation-problems
DanielCortild/PEP-for-SGD-without-Variance
Code implementing the Performance Estimation Problem (PEP) methodology for SGD without variance assumption.
Language: Jupyter Notebook - Size: 453 KB - Last synced at: 8 days ago - Pushed at: 8 days ago - Stars: 0 - Forks: 0
PerformanceEstimation/PEPit
PEPit is a package enabling computer-assisted worst-case analyses of first-order optimization methods.
Language: Python - Size: 2.91 MB - Last synced at: 21 days ago - Pushed at: 5 months ago - Stars: 88 - Forks: 14
PerformanceEstimation/Performance-Estimation-Toolbox
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.
Language: MATLAB - Size: 2.92 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 49 - Forks: 6