AI RESEARCH
RA-DCA: A Randomized Active-Set DCA for Directional Stationarity in Max-Structured DC Programs
arXiv CS.AI
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ArXi:2605.23550v1 Announce Type: cross We study nonsmooth difference-of-convex programs whose subtracted convex term is a finite maximum of smooth convex functions. In this setting, standard DCA iterations may converge to critical points that are not directionally stationary, whereas exact active-vertex screening can be expensive when active sets are large or combinatorial.