17 citations · 23 across the 3 of their papers we have counts for
3 papers
cs.LG2023★ 17 cited
Green Federated Learning
Ashkan Yousefpour, Shen Guo, Ashish Shenoy +7
The rapid progress of AI is fueled by increasingly large and computationally intensive machine learning models and datasets. As a consequence, the amount of compute used in trainin…
cs.LG2023★ 2 cited
Efficient Training of Large-scale Industrial Fault Diagnostic Models through Federated Opportunistic Block Dropout
Yuanyuan Chen, Zichen Chen, Sheng Guo +6
Artificial intelligence (AI)-empowered industrial fault diagnostics is important in ensuring the safe operation of industrial applications. Since complex industrial systems often i…
cs.LG2022★ 4 cited
Personalized Federated Learning for Multi-task Fault Diagnosis of Rotating Machinery
Sheng Guo, Zengxiang Li, Hui Liu +2
Intelligent fault diagnosis is essential to safe operation of machinery. However, due to scarce fault samples and data heterogeneity in field machinery, deep learning based diagnos…