PipeSFL: A Fine-Grained Parallelization Framework for Split Federated Learning on Heterogeneous Clients
Split Federated Learning (SFL) improves scalability of Split Learning (SL) by enabling parallel computing of the learning tasks on multiple clients. However, […]
Semantics Alignment Via Split Learning for Resilient Multi-User Semantic Communication
Recent studies on semantic communication commonly rely on neural network (NN) based transceivers such as deep joint source and channel coding (DeepJSCC). […]
Predictive Closed-Loop Remote Control Over Wireless Two-Way Split Koopman Autoencoder
Real-time remote control over wireless is an important yet challenging application in fifth-generation and beyond due to its mission-critical nature under limited […]