5 citations · 5 across the 5 of their papers we have counts for
5 papers
Hierarchical Federated Foundation Models over Wireless Networks for Multi-Modal Multi-Task Intelligence: Integration of Edge Learning with D2D/P2P-Enabled Fog Learning Architectures
Payam Abdisarabshali, Fardis Nadimi, Kasra Borazjani +6
The rise of foundation models (FMs) has reshaped the landscape of machine learning. As these models continued to grow, leveraging geo-distributed data from wireless devices has bec…
Lightweight and Self-Evolving Channel Twinning: An Ensemble DMD-Assisted Approach
Yashuai Cao, Jintao Wang, Xu Shi +1
Traditional channel acquisition faces significant limitations due to ideal model assumptions and scalability challenges. A novel environment-aware paradigm, known as channel twinni…
ByCAN: Reverse Engineering Controller Area Network (CAN) Messages from Bit to Byte Level
Xiaojie Lin, Baihe Ma, Xu Wang +4
As the primary standard protocol for modern cars, the Controller Area Network (CAN) is a critical research target for automotive cybersecurity threats and autonomous applications.…
Balancing Performance and Cost for Two-Hop Cooperative Communications: Stackelberg Game and Distributed Multi-Agent Reinforcement Learning
Yuanzhe Geng, Erwu Liu, Wei Ni +5
This paper aims to balance performance and cost in a two-hop wireless cooperative communication network where the source and relays have contradictory optimization goals and make d…
Dual-Segment Clustering Strategy for Hierarchical Federated Learning in Heterogeneous Wireless Environments
Pengcheng Sun, Erwu Liu, Wei Ni +6
Non-independent and identically distributed (Non- IID) data adversely affects federated learning (FL) while heterogeneity in communication quality can undermine the reliability of…