Personalized Classifiers from Ensemble learning with Gaussian Process
Personalized Federated Learning with Gaussian Processes Idan Achituve, Aviv Shamsian, Aviv Navon, Gal Chechik, Ethan Fetaya This is a theoretical work for personalized learning with limited data. It was shown that the disadvantage of restricted exposure for each “person” or client can be remediated by learning a shared kernel function across all clients. This is Read more..
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