Search Results for author:
Found 3 papers, 2 papers with code
A Stochastic Proximal Polyak Step Size
Developing a proximal variant of SPS is particularly important, since SPS requires a lower bound of the objective function to work well.
A Semismooth Newton Stochastic Proximal Point Algorithm with Variance Reduction
We develop an implementable stochastic proximal point (SPP) method for a class of weakly convex, composite optimization problems.
A Stochastic Semismooth Newton Method for Nonsmooth Nonconvex Optimization
In this work, we present a globalized stochastic semismooth Newton method for solving stochastic optimization problems involving smooth nonconvex and nonsmooth convex terms in the objective function.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
