A proximal optimization solver in Python for solving objectives including a smooth and a non-smooth part.
If the objective is a convex one, the solver gives a optimal solution.
For an objective min_x f(x)+g(x), one needs to provide a function that computes the function value
of the objective f(x) and its gradient \nabla f(x), and another function computes the proximal operator
associated with g(x): min_x ||x - x'|| + g(x), given x'.
jiayuzhou/pyProxSolver
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