QSplitFL: Capability Aware Deep Q-Learning for Optimal Split Point Selection in Split Federated Learning
QSplitFL introduces a Deep Q-Network framework that optimizes split point selection in federated learning by considering device heterogeneity, using lightweight hardware metrics instead of model weights. The approach demonstrates improved convergence and accuracy across multiple datasets and neural network architectures while adapting to varying client capabilities.