Nonasymptotic convergence of stochastic proximal point algorithms for constrained convex optimization

Andrei Patrascu, Ion Necoara

A very popular approach for solving stochastic optimization problems is the stochastic gradient descent method (SGD). Although the SGD iteration is computationally cheap and the pr…