1 citations · 1 across the 3 of their papers we have counts for
3 papers
math.OC2024
A distributed Douglas-Rachford splitting method for solving linear constrained multi-block weakly convex problems
Leyu Hu, Jiaxin Xie, Xingju Cai +1
In recent years, a distributed Douglas-Rachford splitting method (DDRSM) has been proposed to tackle multi-block separable convex optimization problems. This algorithm offers relat…
cs.LG2024★ 1 cited
Novel clustered federated learning based on local loss
Endong Gu, Yongxin Chen, Hao Wen +2
This paper proposes LCFL, a novel clustering metric for evaluating clients' data distributions in federated learning. LCFL aligns with federated learning requirements, accurately a…
math.OC2023
Understanding the convergence of the preconditioned PDHG method: a view of indefinite proximal ADMM
Yumin Ma, Xingju Cai, Bo Jiang +1
The primal-dual hybrid gradient (PDHG) algorithm is popular in solving min-max problems which are being widely used in a variety of areas. To improve the applicability and efficien…