3 citations · 3 across the 1 of their papers we have counts for
6 papers
Geometric Convergence of Gradient Play Algorithms for Distributed Nash Equilibrium Seeking
Tatiana Tatarenko, Wei Shi, Angelia Nedich
We study distributed algorithms for seeking a Nash equilibrium in a class of non-cooperative convex games with strongly monotone mappings. Each player has access to her own smooth…
Push-Pull Gradient Methods for Distributed Optimization in Networks
Shi Pu, Wei Shi, Jinming Xu +1
In this paper, we focus on solving a distributed convex optimization problem in a network, where each agent has its own convex cost function and the goal is to minimize the sum of…
Accelerating Incremental Gradient Optimization with Curvature Information
Hoi-To Wai, Wei Shi, Cesar A. Uribe +2
This paper studies an acceleration technique for incremental aggregated gradient ({\sf IAG}) method through the use of \emph{curvature} information for solving strongly convex fini…
A Push-Pull Gradient Method for Distributed Optimization in Networks
Shi Pu, Wei Shi, Jinming Xu +1
In this paper, we focus on solving a distributed convex optimization problem in a network, where each agent has its own convex cost function and the goal is to minimize the sum of…
Curvature-aided Incremental Aggregated Gradient Method
Hoi-To Wai, Wei Shi, Angelia Nedic +1
We propose a new algorithm for finite sum optimization which we call the curvature-aided incremental aggregated gradient (CIAG) method. Motivated by the problem of training a class…
A Decentralized Second-Order Method for Dynamic Optimization
Aryan Mokhtari, Wei Shi, Qing Ling +1
This paper considers decentralized dynamic optimization problems where nodes of a network try to minimize a sequence of time-varying objective functions in a real-time scheme. At e…