26 citations · 51 across the 2 of their papers we have counts for
4 papers
Make Workers Work Harder: Decoupled Asynchronous Proximal Stochastic Gradient Descent
Yitan Li, Linli Xu, Xiaowei Zhong +1
Asynchronous parallel optimization algorithms for solving large-scale machine learning problems have drawn significant attention from academia to industry recently. This paper prop…
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…
Network Newton-Part II: Convergence Rate and Implementation
Aryan Mokhtari, Qing Ling, Alejandro Ribeiro
The use of network Newton methods for the decentralized optimization of a sum cost distributed through agents of a network is considered. Network Newton methods reinterpret distrib…
Network Newton-Part I: Algorithm and Convergence
Aryan Mokhtari, Qing Ling, Alejandro Ribeiro
We study the problem of minimizing a sum of convex objective functions where the components of the objective are available at different nodes of a network and nodes are allowed to…