1 citations · 1 across the 5 of their papers we have counts for
6 papers
Sequential Federated Learning in Hierarchical Architecture on Non-IID Datasets
Xingrun Yan, Shiyuan Zuo, Rongfei Fan +4
In a real federated learning (FL) system, communication overhead for passing model parameters between the clients and the parameter server (PS) is often a bottleneck. Hierarchical…
Over-the-Air Computation Aided Federated Learning with the Aggregation of Normalized Gradient
Rongfei Fan, Xuming An, Shiyuan Zuo +1
Over-the-air computation is a communication-efficient solution for federated learning (FL). In such a system, iterative procedure is performed: Local gradient of private loss funct…
Federated Learning Robust to Byzantine Attacks: Achieving Zero Optimality Gap
Shiyuan Zuo, Rongfei Fan, Han Hu +2
In this paper, we propose a robust aggregation method for federated learning (FL) that can effectively tackle malicious Byzantine attacks. At each user, model parameter is firstly…
Joint Power Control and Data Size Selection for Over-the-Air Computation Aided Federated Learning
Xuming An, Rongfei Fan, Shiyuan Zuo +3
Federated learning (FL) has emerged as an appealing machine learning approach to deal with massive raw data generated at multiple mobile devices, {which needs to aggregate the trai…
Joint Task Offloading and Resource Allocation for Streaming Application in Cooperative Mobile Edge Computing
Xiang Li, Rongfei Fan, Han Hu +1
Mobile edge computing (MEC) enables resource-limited IoT devices to complete computation-intensive or delay-sensitive task by offloading the task to adjacent edge server deployed a…
Dynamic Spectrum Leasing with Two Sellers
Rongfei Fan, Wen Chen, Hai Jiang +3
This paper studies dynamic spectrum leasing in a cognitive radio network. There are two spectrum sellers, who are two primary networks, each with an amount of licensed spectrum ban…