Second-Order KKT Guarantees for Bregman ADMM in Nonconvex and Non-Lipschitz Optimization

By Shuang Li · Paper · math.OC

We analyze Bregman ADMM for nonconvex linearly constrained problems under two-sided relative smoothness, a condition that replaces the standard Lipschitz gradient assumption with a Hessian comparison relative to a Bregman kernel. This setting covers polynomial objectives arising

Math.oc

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