Randomized smoothing for stochastic optimization
The convergence rates of stochastic optimization algorithms for nonsmooth convex optimization problems are analyzed. The authors also discuss several applications of the proposed results to statistical estimation problems. Some experimental results are provided to demonstrate the effectiveness of the proposed algorithms.
scientific article; zbMATH DE number 6081241