873 citations · 1.8k across the 33 of their papers we have counts for
6 papers · 1 filter
Byzantine-Resilient Decentralized TD Learning with Linear Function Approximation
Zhaoxian Wu, Han Shen, Tianyi Chen +1
This paper considers the policy evaluation problem in a multi-agent reinforcement learning (MARL) environment over decentralized and directed networks. The focus is on decentralize…
Byzantine-Robust Variance-Reduced Federated Learning over Distributed Non-i.i.d. Data
Jie Peng, Zhaoxian Wu, Qing Ling +1
We consider the federated learning problem where data on workers are not independent and identically distributed (i.i.d.). During the learning process, an unknown number of Byzanti…
A Newton Tracking Algorithm with Exact Linear Convergence Rate for Decentralized Consensus Optimization
Jiaojiao Zhang, Qing Ling, Anthony Man-Cho So
This paper considers the decentralized consensus optimization problem defined over a network where each node holds a second-order differentiable local objective function. Our goal…
Byzantine-Robust Decentralized Stochastic Optimization over Static and Time-Varying Networks
Jie Peng, Weiyu Li, Qing Ling
In this paper, we consider the Byzantine-robust stochastic optimization problem defined over decentralized static and time-varying networks, where the agents collaboratively minimi…
HierTrain: Fast Hierarchical Edge AI Learning with Hybrid Parallelism in Mobile-Edge-Cloud Computing
Deyin Liu, Xu Chen, Zhi Zhou +1
Nowadays, deep neural networks (DNNs) are the core enablers for many emerging edge AI applications. Conventional approaches to training DNNs are generally implemented at central se…
Can Primal Methods Outperform Primal-dual Methods in Decentralized Dynamic Optimization?
Kun Yuan, Wei Xu, Qing Ling
In this paper, we consider the decentralized dynamic optimization problem defined over a multi-agent network. Each agent possesses a time-varying local objective function, and all…