There are 1 repository under proximal-algorithms topic.
The Advanced Proximal Optimization Toolbox
Proximal operators for nonsmooth optimization in Julia
Proximal algorithms for nonsmooth optimization in Julia
A Python convex optimization package using proximal splitting methods
Official code repository for ∇-Prox: Differentiable Proximal Algorithm Modeling for Large-Scale Optimization (SIGGRAPH TOG 2023)
MATLAB library of gradient descent algorithms for sparse modeling: Version 1.0.3
PyProximal – Proximal Operators and Algorithms in Python
A Julia package that solves Linearly Constrained Separable Optimization Problems using ADMM.
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.
A small library implementing phase retrieval algorithms for 2D images.
Proximal Nested Sampling for high-dimensional Bayesian model selection
Cut-pursuit with preconditioned forward-Douglas-Rachford for regularization of classical functionals by graph total variation
Iterative shrinkage / thresholding algorithms (ISTAs) for linear inverse problems
MATLAB implementations of a variety of machine learning/signal processing algorithms.
Coordinate and Incremental Aggregated Optimization Algorithms
Topics in Signal Processing
New Matrix Factorization Algorithms based on Bregman Proximal Gradient: BPG-MF, CoCaIn BPG-MF, BPG-MF-WB
A Python implementation of Goldstein et. al's FASTA algorithm for convex optimization.
Test Cases for Regularized Optimization
Proximal operators for use with RegularizedOptimization
Bazinga.jl: a toolbox for constrained composite optimization
Fast Inertial Algorithm for Phase Retrieval
Implementation of Collective Matrix Completion by Mokhtar Z. Alaya and Olga Klopp https://arxiv.org/abs/1807.09010
Solving inverse problems with Proximal Markov Chain Monte Carlo
Q. Yao, J. Xu, W. Tu, Z. Zhu. Efficient Neural Architecture Search via Proximal Iterations. AAAI 2020.
CoCaIn BPG escapes Spurious Stationary Points
This repository provides Matlab codes related to the paper "Fast reconstruction of sparse relative impulse responses via second-order cone programming" presented at WASPAA 2017 workshop
A Python implementation of Generalized Fused Lasso from https://arxiv.org/pdf/1801.05413.pdf
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.