AdrienTaylor

AccelerationMethodsWebsite

BnB-PEP-code

conv_arithmetic

A technical report on convolution arithmetic in the context of deep learning

opera-python

opera

Online Prediction by ExpeRt Aggregation

notebook-progress-tracker

Track progress in jupyter notebooks

qpsolvers

Quadratic programming solvers in Python with a unified API

cycles

TightLyapunovAnalysis

NCG-PEP-code

QG

proxsuite

The Advanced Proximal Optimization Toolbox

Learning-Performance-Estimation

This repository regroups learning ressources about performance estimation problems

sedumi

SeDuMi: A linear/quadratic/semidefinite solver for Matlab and Octave

YALMIP

MATLAB toolbox for optimization modeling

potentials_and_last_iter_convergence_for_VIPs

osqp

The Operator Splitting QP Solver

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.

test

PEPit

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

2021-measures-PGM

Code for the paper "Convergence Rates of Gradient Methods for Convex Optimization in the Space of Measures"

BregmanPerformanceEstimation

Performance Estimation Problem for Bregman first order methods

InexactProximalOperators

Code associated with the work "Principled Analyses and Design of First-order Methods with Inexact Proximal Operators".