3 papers
cs.DC2026
Breaking the Capacity Bottleneck in Model-Heterogeneous Federated Learning via Gradual Model Restoration
Chengjie Ma, Seungeun Oh, Jihong Park +1
Federated learning (FL) enables distributed model training, yet in heterogeneous deployments, Bandwidth-Constrained Clients (BCCs) often contribute inefficiently due to limited upl…
cs.RO2025
Action Deviation-Aware Inference for Low-Latency Wireless Robots
Jeyoung Park, Yeonsub Lim, Seungeun Oh +3
To support latency-sensitive AI applications ranging from autonomous driving to industrial robot manipulation, 6G envisions distributed ML with computational resources in mobile, e…
eess.SY2025
Deadline-Aware Bandwidth Allocation for Semantic Generative Communication with Diffusion Models
Jinhyuk Choi, Jihong Park, Seungeun Oh +1
The importance of Radio Access Network (RAN) in support Artificial Intelligence (AI) application services has grown significantly, underscoring the need for an integrated approach…