79 citations · 218 across the 34 of their papers we have counts for
4 papers · 1 filter
Deep Reinforcement Learning Based Vehicle Selection for Asynchronous Federated Learning Enabled Vehicular Edge Computing
Qiong Wu, Siyuan Wang, Pingyi Fan +1
In the traditional vehicular network, computing tasks generated by the vehicles are usually uploaded to the cloud for processing. However, since task offloading toward the cloud wi…
FedLP: Layer-wise Pruning Mechanism for Communication-Computation Efficient Federated Learning
Zheqi Zhu, Yuchen Shi, Jiajun Luo +4
Federated learning (FL) has prevailed as an efficient and privacy-preserved scheme for distributed learning. In this work, we mainly focus on the optimization of computation and co…
Convergence Analysis and System Design for Federated Learning over Wireless Networks
Shuo Wan, Jiaxun Lu, Pingyi Fan +3
Federated learning (FL) has recently emerged as an important and promising learning scheme in IoT, enabling devices to jointly learn a model without sharing their raw data sets. Ho…
MIM-Based GAN: Information Metric to Amplify Small Probability Events Importance in Generative Adversarial Networks
Rui She, Pingyi Fan
In terms of Generative Adversarial Networks (GANs), the information metric to discriminate the generative data from the real data, lies in the key point of generation efficiency, w…