3 papers
cs.LG2025
Pigeon-SL: Robust Split Learning Framework for Edge Intelligence under Malicious Clients
Sangjun Park, Tony Q. S. Quek, Hyowoon Seo
Recent advances in split learning (SL) have established it as a promising framework for privacy-preserving, communication-efficient distributed learning at the network edge. Howeve…
eess.SP2025
Distribution-Level AirComp for Wireless Federated Learning under Data Scarcity and Heterogeneity
Jun-Pyo Hong, Hyowoon Seo, Kisong Lee
The conventional FL methods face critical challenges in realistic wireless edge networks, where training data is both limited and heterogeneous, often leading to unstable training…
eess.SP2025
Federated Learning Meets Fluid Antenna: Towards Robust and Scalable Edge Intelligence
Sangjun Park, Hyowoon Seo
Federated learning (FL) is an emerging machine learning paradigm with immense potential to support advanced services and applications in future industries. However, when deployed o…