Matlab and Python toolbox for fast Total Variation proximity operators

MATLAB library of gradient descent algorithms for sparse modeling: Version 1.0.3

A Python convex optimization package using proximal splitting methods

Proximal operators for nonsmooth optimization in Julia

Proximal algorithms for nonsmooth optimization in Julia

A Matlab convex optimization toolbox using proximal splitting methods

Scientific Computational Imaging COde

Implementation of "Learning Proximal Operators: Using Denoising Networks for Regularizing Inverse Imaging Problems"

Python routines to compute the Total Variation (TV) of 2D, 3D and 4D images on CPU & GPU. Compatible with proximal algorithms (ADMM, Chambolle & Pock, ...)

Test Cases for Regularized Optimization

New Matrix Factorization Algorithms based on Bregman Proximal Gradient: BPG-MF, CoCaIn BPG-MF, BPG-MF-WB

Primal-Dual Solver for Inverse Problems

A Julia package that solves Linearly Constrained Separable Optimization Problems using ADMM.

MATLAB implementations of a variety of machine learning/signal processing algorithms.

Hybrid Approach to Sparse Group Fused Lasso

A Julia package for manipulation of univariate piecewise quadratic functions.

A Python package which implements the Elastic Net using the (accelerated) proximal gradient method.

Provides proximal operator evaluation routines and proximal optimization algorithms, such as (accelerated) proximal gradient methods and alternating direction method of multipliers (ADMM), for non-smooth/non-differentiable objective functions.

Codes of `Tensor Robust Principal Component Analysis` expreiments. Besides, this repo is for my own convex optimization assignments, so do not copy for your assignments !!!

Nonlinear Power Method for Computing Eigenvectors of Proximal Operators and Neural Networks