Proximal algorithms for nonsmooth optimization in Julia
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Updated
Jan 5, 2025 - Julia
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).
Proximal Gradient/Semismooth Newton Methods for Projection onto a Polyhedron via the Duality-Gap-Active-Set Strategy
Implementation and brief comparison of different First Order and different Proximal gradient methods, comparison of their convergence rates
[Optimization algorithms] Study of the Proximal Gradient Method, Stochastic Gradient Descent method and Adam optimizer
Regularized methods for efficient ranking in networks
Unified implementation of MGProx.
Approximate Bregman proximal gradient algorithm
Some notes on convex optimization
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