3 papers
cs.LG2026
FedRD: Reducing Divergences for Generalized Federated Learning via Heterogeneity-aware Parameter Guidance
Kaile Wang, Jiannong Cao, Yu Yang +2
Heterogeneous federated learning (HFL) aims to ensure effective and privacy-preserving collaboration among different entities. As newly joined clients require significant adjustmen…
cs.LG2026
FedCCA: Client-Centric Adaptation against Data Heterogeneity in Federated Learning on IoT Devices
Kaile Wang, Jiannong Cao, Yu Yang +2
With the rapid development of the Internet of Things (IoT), AI model training on private data such as human sensing data is highly desired. Federated learning (FL) has emerged as a…
cs.CY2024
DMP_AI: An AI-Aided K-12 System for Teaching and Learning in Diverse Schools
Zhen-Qun Yang, Jiannong Cao, Xiaoyin Li +4
The use of Artificial Intelligence (AI) has gained momentum in education. However, the use of AI in K-12 education is still in its nascent stages, and further research and developm…