6 citations · 23 across the 13 of their papers we have counts for
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cs.LG2022★ 6 cited
Resource-Aware Heterogeneous Federated Learning using Neural Architecture Search
Sixing Yu, J. Pablo Muñoz, Ali Jannesari
Federated Learning (FL) is extensively used to train AI/ML models in distributed and privacy-preserving settings. Participant edge devices in FL systems typically contain non-indep…
cs.DC2022★ 5 cited
Enhancing Heterogeneous Federated Learning with Knowledge Extraction and Multi-Model Fusion
Duy Phuong Nguyen, Sixing Yu, J. Pablo Muñoz +1
Concerned with user data privacy, this paper presents a new federated learning (FL) method that trains machine learning models on edge devices without accessing sensitive data. Tra…