42 citations · 163 across the 36 of their papers we have counts for
4 papers · 1 filter
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…
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…
Mirror Natural Evolution Strategies
Haishan Ye
The zeroth-order optimization has been widely used in machine learning applications. However, the theoretical study of the zeroth-order optimization focus on the algorithms which a…
Stochastic Distributed Optimization under Average Second-order Similarity: Algorithms and Analysis
Dachao Lin, Yuze Han, Haishan Ye +1
We study finite-sum distributed optimization problems involving a master node and local nodes under the popular -similarity and -strong convexity conditions. We propose…