Stochastic minimax problems

Projection-Free Algorithms for Nonsmooth Stochastic Convex-Concave Saddle-Point Problems

Categories Convex and Nonsmooth Optimization, Convex Optimization Tags , , ,

We study nonsmooth convex-concave saddle-point problems over compact convex sets, assuming access to stochastic subgradients of the payoff function. We develop single-loop projection-free algorithms that use linear minimization oracles over the primal and dual domains. Unlike prior projection-free approaches that rely on smoothing, our methods are purely subgradient-based and handle nonsmoothness directly. This design makes … Read more

Zeroth-Order Methods for Nonconvex-Strongly Concave Stochastic Minimax Problems with Decision-Dependent Distributions

Categories Nonlinear Optimization, Optimization in Data Science, Stochastic Programming Tags , , , ,

Stochastic minimax problems with decision-dependent distributions (SMDD) have emerged as a crucial framework for modeling complex systems where data distributions drift in response to decision variables. Most existing methods for SMDD rely on an explicit functional relationship between the decision variables and the probability distribution. In this paper, we propose two sample-based zeroth-order algorithms, namely … Read more