The Advanced Proximal Optimization Toolbox
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Updated
May 6, 2024 - C++
The Advanced Proximal Optimization Toolbox
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 optimization in pure python
A Matlab convex optimization toolbox using proximal splitting methods
Proximal algorithms for nonsmooth optimization in Julia
Scientific Computational Imaging COde
PyProximal – Proximal Operators and Algorithms in Python
A set of notebooks related to convex optimization, variational inference and numerical methods for signal processing, machine learning, deep learning, graph analysis, bayesian programming, statistics or astronomy.
Proximal operators for use with RegularizedOptimization
Official code repository for ∇-Prox: Differentiable Proximal Algorithm Modeling for Large-Scale Optimization (SIGGRAPH TOG 2023)
A small library implementing phase retrieval algorithms for 2D images.
A Python implementation of Goldstein et. al's FASTA algorithm for convex optimization.
Test Cases for Regularized Optimization
Cut-pursuit with preconditioned forward-Douglas-Rachford for regularization of classical functionals by graph total variation
New Matrix Factorization Algorithms based on Bregman Proximal Gradient: BPG-MF, CoCaIn BPG-MF, BPG-MF-WB
Coordinate and Incremental Aggregated Optimization Algorithms
A Julia package that solves Linearly Constrained Separable Optimization Problems using ADMM.
MATLAB implementations of a variety of machine learning/signal processing algorithms.
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