873 citations · 1.3k across the 35 of their papers we have counts for
4 papers · 1 filter
Decentralized Proximal Gradient Algorithms with Linear Convergence Rates
Sulaiman A. Alghunaim, Ernest K. Ryu, Kun Yuan +1
This work studies a class of non-smooth decentralized multi-agent optimization problems where the agents aim at minimizing a sum of local strongly-convex smooth components plus a c…
ODE Analysis of Stochastic Gradient Methods with Optimism and Anchoring for Minimax Problems
Ernest K. Ryu, Kun Yuan, Wotao Yin
Despite remarkable empirical success, the training dynamics of generative adversarial networks (GAN), which involves solving a minimax game using stochastic gradients, is still poo…
A Linearly Convergent Proximal Gradient Algorithm for Decentralized Optimization
Sulaiman A. Alghunaim, Kun Yuan, Ali H. Sayed
Decentralized optimization is a powerful paradigm that finds applications in engineering and learning design. This work studies decentralized composite optimization problems with n…
On the Influence of Bias-Correction on Distributed Stochastic Optimization
Kun Yuan, Sulaiman A. Alghunaim, Bicheng Ying +1
Various bias-correction methods such as EXTRA, gradient tracking methods, and exact diffusion have been proposed recently to solve distributed {\em deterministic} optimization prob…