distributionally robust optimization 1minimax 1nonconvex-nonconcave 1smoothing methods 1stochastic optimization 1
From the 1 of 2 linked papers with an AI index.
2 papers
math.OC2026
A stochastic smoothing framework for nonconvex-nonconcave minEmax problems with applications to Wasserstein distributionally robust optimization
Wei Liu, Muhammad Khan, Gabriel Mancino-Ball +1
The paper introduces a stochastic smoothing proximal gradient algorithm for solving nonconvex‑nonconcave minimization‑expectation‑maximization (minEmax) problems, providing converg…
math.OC2026
A variance reduced framework for (non)smooth nonconvex-nonconcave stochastic minimax problems with extended Kurdyka-Lojasiewicz property
Muhammad Khan, Yangyang Xu
In this paper, we study stochastic constrained minimax optimization problems with nonconvex-nonconcave structure, a central problem in modern machine learning, for which reliable a…