3 papers
cs.AI2025
NeuroGen: Neural Network Parameter Generation via Large Language Models
Jiaqi Wang, Yusen Zhang, Xi Li
Acquiring the parameters of neural networks (NNs) has been one of the most important problems in machine learning since the inception of NNs. Traditional approaches, such as backpr…
cs.DC2024
Bridging Model Heterogeneity in Federated Learning via Uncertainty-based Asymmetrical Reciprocity Learning
Jiaqi Wang, Chenxu Zhao, Lingjuan Lyu +3
This paper presents FedType, a simple yet pioneering framework designed to fill research gaps in heterogeneous model aggregation within federated learning (FL). FedType introduces…
cs.LG2024
Leveraging Foundation Models for Multi-modal Federated Learning with Incomplete Modality
Liwei Che, Jiaqi Wang, Xinyue Liu +1
Federated learning (FL) has obtained tremendous progress in providing collaborative training solutions for distributed data silos with privacy guarantees. However, few existing wor…