3 papers
cs.LG2025
Privacy-Enhanced Training-as-a-Service for On-Device Intelligence: Concept, Architectural Scheme, and Open Problems
Zhiyuan Wu, Sheng Sun, Yuwei Wang +4
On-device intelligence (ODI) enables artificial intelligence (AI) applications to run on end devices, providing real-time and customized AI inference without relying on remote serv…
cs.DC2024
Agglomerative Federated Learning: Empowering Larger Model Training via End-Edge-Cloud Collaboration
Zhiyuan Wu, Sheng Sun, Yuwei Wang +5
Federated Learning (FL) enables training Artificial Intelligence (AI) models over end devices without compromising their privacy. As computing tasks are increasingly performed by a…
cs.LG2024
Federated Class-Incremental Learning with New-Class Augmented Self-Distillation
Zhiyuan Wu, Tianliu He, Sheng Sun +4
Federated Learning (FL) enables collaborative model training among participants while guaranteeing the privacy of raw data. Mainstream FL methodologies overlook the dynamic nature…