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math.OC2023
Optimal Decentralized Composite Optimization for Convex Functions
Haishan Ye, Xiangyu Chang
In this paper, we focus on the decentralized composite optimization for convex functions. Because of advantages such as robust to the network and no communication bottle-neck in th…
math.OC2023★ 1 cited
Decentralized Riemannian Conjugate Gradient Method on the Stiefel Manifold
Jun Chen, Haishan Ye, Mengmeng Wang +4
The conjugate gradient method is a crucial first-order optimization method that generally converges faster than the steepest descent method, and its computational cost is much lowe…