activity
20222025
most citedHierarchical Personalized Federated Learning Over Massive Mobile Edge Computing Networks

41 citations · 65 across the 5 of their papers we have counts for

collaborators

5 papers

cs.NI2025

FlexSAN: A Flexible Regenerative Satellite Access Network Architecture

Weize Kong, Chaoqun You, Xuming Pei +1

The regenerative satellite access network (SAN) architecture deploys next-generation NodeB (gNBs) on satellites to enable enhanced network management capabilities. It supports two…

cs.LG2025

Communication and Computation Efficient Split Federated Learning in O-RAN

Shunxian Gu, Chaoqun You, Bangbang Ren +1

The hierarchical architecture of Open Radio Access Network (O-RAN) has enabled a new Federated Learning (FL) paradigm that trains models using data from non- and near-real-time (ne…

cs.LG202312 cited

Automated Federated Learning in Mobile Edge Networks -- Fast Adaptation and Convergence

Chaoqun You, Kun Guo, Gang Feng +2

Federated Learning (FL) can be used in mobile edge networks to train machine learning models in a distributed manner. Recently, FL has been interpreted within a Model-Agnostic Meta…

cs.LG202341 cited

Hierarchical Personalized Federated Learning Over Massive Mobile Edge Computing Networks

Chaoqun You, Kun Guo, Howard H. Yang +1

Personalized Federated Learning (PFL) is a new Federated Learning (FL) paradigm, particularly tackling the heterogeneity issues brought by various mobile user equipments (UEs) in m…

cs.NI202212 cited

Hierarchical Multi-resource Fair Queueing for Packet Processing

C. You, Y. Zhao, G. Feng +2

Various middleboxes are ubiquitously deployed in networks to perform packet processing functions, such as firewalling, proxy, scheduling, etc., for the flows passing through them.…