Proximal algorithms for nonsmooth optimization in Julia

Iterative shrinkage / thresholding algorithms (ISTAs) for linear inverse problems

A Julia package for adaptive proximal gradient and primal-dual algorithms

Test Cases for Regularized Optimization

Accelerated Proximal Gradient (APG) algorithm implementation for Nuclear Norm regularized linear Least Squares problem (NNLS).

Sparse optimal control of the Viscous Cahn-Hilliard equation using Proximal Gradient Descent. Solved with Crank-Nicolson semi-implicit time integration.

Implementation and brief comparison of different First Order and different Proximal gradient methods, comparison of their convergence rates

Proximal Gradient/Semismooth Newton Methods for Projection onto a Polyhedron via the Duality-Gap-Active-Set Strategy

[Optimization algorithms] Study of the Proximal Gradient Method, Stochastic Gradient Descent method and Adam optimizer

Use neural network proximal gradient to guide a fuzzer’s input selection

Regularized methods for efficient ranking in networks

Some notes on convex optimization

Approximate Bregman proximal gradient algorithm

Unified implementation of MGProx.