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arXiv Machine Learning By Yuchen Xin, Zhihua Zhang

Active-Trace Complexity Bounds for Moreau--Yosida Unadjusted Langevin Sampling

Read the original on arXiv Machine Learning →

arXiv:2608. 13467v1 Announce Type: new Abstract: We study the Moreau--Yosida unadjusted Langevin algorithm (MYULA) for the nonsmooth composite target \[ \pi(dx)\propto \exp\{-f(x)-g(x)\}\,dx, \qquad x\in\mathbb R^d, \] where \(f\) is \(m\)-strongly convex with \(L_f\)-Lipschitz gradient and \(g\) is convex and \(G\)-Lipschitz.

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