Modeling language and tools for constrained, structured optimization problems
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Updated
Jan 20, 2022 - Julia
Modeling language and tools for constrained, structured optimization problems
Fortran code implementing Newton-like algorithms for proximal mapping of total variation.
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 !!!
A C/x86 assembly implementation of proximal operators with SSE3/AVX SIMD instructions
A Python package which implements the Elastic Net using the (accelerated) proximal gradient method.
Nonlinear Power Method for Computing Eigenvectors of Proximal Operators and Neural Networks
CoCaIn BPG escapes Spurious Stationary Points
An efficient GPU-compatible library built on PyTorch, offering a wide range of proximal operators and constraints for optimization and machine learning tasks.
Hybrid Approach to Sparse Group Fused Lasso
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
MATLAB implementations of a variety of machine learning/signal processing algorithms.
A Julia package for manipulation of univariate piecewise quadratic functions.
A Julia package that solves Linearly Constrained Separable Optimization Problems using ADMM.
Python routines to compute the Total Variation (TV) of 2D, 3D and 4D images on CPU & GPU. Compatible with proximal algorithms (ADMM, Chambolle & Pock, ...)
Implementation of "Learning Proximal Operators: Using Denoising Networks for Regularizing Inverse Imaging Problems"
A Matlab convex optimization toolbox using proximal splitting methods
MATLAB library of gradient descent algorithms for sparse modeling: Version 1.0.3
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