6 papers
DAMA: A Unified Accelerated Approach for Decentralized Nonconvex Minimax Optimization-Part II: Convergence and Performance Analyses
Haoyuan Cai, Sulaiman A. Alghunaim, Ali H. Sayed
In Part I of this work [1], we developed an accelerated algorithmic framework, DAMA (Decentralized Accelerated Minimax Approach), for nonconvex Polyak-Lojasiewicz (PL) minimax opti…
DAMA: A Unified Accelerated Approach for Decentralized Nonconvex Minimax Optimization-Part I: Algorithm Development and Results
Haoyuan Cai, Sulaiman A. Alghunaim, Ali H. Sayed
In this work and its accompanying Part II [1], we develop an accelerated algorithmic framework, DAMA (Decentralized Accelerated Minimax Approach), for nonconvex Polyak-Lojasiewicz…
Communication-Efficient Decentralized Stochastic Minimax Optimization
Haoyuan Cai, Sulaiman A. Alghunaim, Ali H. Sayed
In this work, we study decentralized stochastic nonconvex Polyak--Łojasiewicz minimax problems and propose a communication-efficient algorithm. Motivated by the efficiency of local…
Diffusion Stochastic Learning Over Adaptive Competing Networks
Yike Zhao, Haoyuan Cai, Ali H. Sayed
This paper studies a stochastic dynamic game between two competing teams, each consisting of a network of collaborating agents. Unlike fully cooperative settings, where all agents…
Accelerated Stochastic Min-Max Optimization Based on Bias-corrected Momentum
Haoyuan Cai, Sulaiman A. Alghunaim, Ali H. Sayed
Lower-bound analyses for nonconvex strongly-concave minimax optimization problems have shown that stochastic first-order algorithms require at least …
Diffusion Stochastic Optimization for Min-Max Problems
Haoyuan Cai, Sulaiman A. Alghunaim, Ali H. Sayed
The optimistic gradient method is useful in addressing minimax optimization problems. Motivated by the observation that the conventional stochastic version suffers from the need fo…