no code implementations • 2 Dec 2023 • Junwen Qiu, Xiao Li, Andre Milzarek
In this work, we design a new normal map-based proximal random reshuffling (norm-PRR) method for nonsmooth nonconvex finite-sum problems.
no code implementations • 10 May 2023 • Andre Milzarek, Junwen Qiu
In this paper, we present a novel stochastic normal map-based algorithm ($\mathsf{norM}\text{-}\mathsf{SGD}$) for nonconvex composite-type optimization problems and discuss its convergence properties.
no code implementations • 31 Dec 2021 • Kun Huang, Xiao Li, Andre Milzarek, Shi Pu, Junwen Qiu
We show that D-RR inherits favorable characteristics of RR for both smooth strongly convex and smooth nonconvex objective functions.
no code implementations • 10 Oct 2021 • Xiao Li, Andre Milzarek, Junwen Qiu
We conduct a novel convergence analysis for the non-descent RR method with diminishing step sizes based on the KL inequality, which generalizes the standard KL framework.