Proximal algorithms (also known as "splitting" algorithms or methods) for nonsmooth optimization in Julia.
This package can be used in combination with ProximalOperators.jl (providing first-order primitives, i.e. gradient and proximal mapping, for numerous cost functions) and AbstractOperators.jl (providing several linear and nonlinear operators) to formulate and solve a wide spectrum of nonsmooth optimization problems.
|Asymmetric forward-backward-adjoint algorithm||
|Chambolle-Pock primal dual algorithm||
|Douglas-Rachford splitting algorithm||
|Forward-backward splitting (i.e. proximal gradient) algorithm||
|Vũ-Condat primal-dual algorithm||
Contributions are welcome in the form of issues notification or pull requests. We recommend looking at already implemented algorithms, or following the template, to get inspiration on how to structure new ones.
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