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Distributed Random Reshuffling over Networks. (arXiv:2112.15287v1 [math.OC])
Jan. 3, 2022, 2:10 a.m. | Kun Huang, Xiao Li, Andre Milzarek, Shi Pu, Junwen Qiu
cs.LG updates on arXiv.org arxiv.org
In this paper, we consider the distributed optimization problem where $n$
agents, each possessing a local cost function, collaboratively minimize the
average of the local cost functions over a connected network. To solve the
problem, we propose a distributed random reshuffling (D-RR) algorithm that
combines the classical distributed gradient descent (DGD) method and Random
Reshuffling (RR). We show that D-RR inherits the superiority of RR for both
smooth strongly convex and smooth nonconvex objective functions. In particular,
for smooth strongly …
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