3 papers
math.OC2026
State-space models through the lens of ensemble control
Ye Feng, Jianfeng Lu
State-space models (SSMs) are effective architectures for sequential modeling, but a rigorous theoretical understanding of their training dynamics is still lacking. In this work, w…
cs.LG2024
FedCross: Intertemporal Federated Learning Under Evolutionary Games
Jianfeng Lu, Ying Zhang, Riheng Jia +3
Federated Learning (FL) mitigates privacy leakage in decentralized machine learning by allowing multiple clients to train collaboratively locally. However, dynamic mobile networks…
cs.LG2024
TRAIL: Trust-Aware Client Scheduling for Semi-Decentralized Federated Learning
Gangqiang Hu, Jianfeng Lu, Jianmin Han +3
Due to the sensitivity of data, Federated Learning (FL) is employed to enable distributed machine learning while safeguarding data privacy and accommodating the requirements of var…