Reinforcement Learning-based Resource-Aware Adaptive Inference for Heterogeneous Split Federated Learning
Heterogeneous Split Federated Learning (HSFL) is a privacy-preserving technique for devices in different edge settings. However, the present methods adopt a static model partition that cannot adapt to network conditions, resulting in longer inference latency and higher communication costs. To address this issue, we pro...