AI RESEARCH

A first-order method for constrained nonconvex-nonconcave minimax optimization

arXiv CS.LG

ArXi:2510.01168v3 Announce Type: replace-cross We study a class of constrained nonconvex-nonconcave minimax optimization problems in which the inner maximization involves potentially complex constraints. Under the assumption that the inner problem of a novel lifted minimax reformulation satisfies a local Kurdyka-Lojasiewicz (KL) condition, we show that the maximal function of the original problem enjoys a local generalized H\"{o}lder smoothness property.