63 citations · 183 across the 24 of their papers we have counts for
4 papers · 2 filters
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…
FedCache: A Knowledge Cache-driven Federated Learning Architecture for Personalized Edge Intelligence
Zhiyuan Wu, Sheng Sun, Yuwei Wang +6
Edge Intelligence (EI) allows Artificial Intelligence (AI) applications to run at the edge, where data analysis and decision-making can be performed in real-time and close to data…
FedBIAD: Communication-Efficient and Accuracy-Guaranteed Federated Learning with Bayesian Inference-Based Adaptive Dropout
Jingjing Xue, Min Liu, Sheng Sun +3
Federated Learning (FL) emerges as a distributed machine learning paradigm without end-user data transmission, effectively avoiding privacy leakage. Participating devices in FL are…
FedTrip: A Resource-Efficient Federated Learning Method with Triplet Regularization
Xujing Li, Min Liu, Sheng Sun +3
In the federated learning scenario, geographically distributed clients collaboratively train a global model. Data heterogeneity among clients significantly results in inconsistent…