3 citations · 5 across the 6 of their papers we have counts for
6 papers
FitLight: Federated Imitation Learning for Plug-and-Play Autonomous Traffic Signal Control
Yutong Ye, Yingbo Zhou, Zhusen Liu +4
Although Reinforcement Learning (RL)-based Traffic Signal Control (TSC) methods have been extensively studied, their practical applications still raise some serious issues such as…
SAFL: Structure-Aware Personalized Federated Learning via Client-Specific Clustering and SCSI-Guided Model Pruning
Nan Li, Xiaolu Wang, Xiao Du +2
Federated Learning (FL) enables clients to collaboratively train machine learning models without sharing local data, preserving privacy in diverse environments. While traditional F…
PET: Multi-agent Independent PPO-based Automatic ECN Tuning for High-Speed Data Center Networks
Kai Cheng, Ting Wang, Xiao Du +2
Explicit Congestion Notification (ECN)-based congestion control schemes have been widely adopted in high-speed data center networks (DCNs), where the ECN marking threshold plays a…
When Foresight Pruning Meets Zeroth-Order Optimization: Efficient Federated Learning for Low-Memory Devices
Pengyu Zhang, Yingjie Liu, Yingbo Zhou +4
Although Federated Learning (FL) enables collaborative learning in Artificial Intelligence of Things (AIoT) design, it fails to work on low-memory AIoT devices due to its heavy mem…
Situation-Dependent Causal Influence-Based Cooperative Multi-agent Reinforcement Learning
Xiao Du, Yutong Ye, Pengyu Zhang +3
Learning to collaborate has witnessed significant progress in multi-agent reinforcement learning (MARL). However, promoting coordination among agents and enhancing exploration capa…
Multi-agent Reinforcement Learning for Dynamic Resource Management in 6G in-X Subnetworks
Xiao Du, Ting Wang, Qiang Feng +4
The 6G network enables a subnetwork-wide evolution, resulting in a "network of subnetworks". However, due to the dynamic mobility of wireless subnetworks, the data transmission of…