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cs.LG2023
Federated Variational Inference: Towards Improved Personalization and Generalization
Elahe Vedadi, Joshua V. Dillon, Philip Andrew Mansfield +3
Conventional federated learning algorithms train a single global model by leveraging all participating clients' data. However, due to heterogeneity in client generative distributio…
cs.DC2023
Efficient Coded Multi-Party Computation at Edge Networks
Elahe Vedadi, Yasaman Keshtkarjahromi, Hulya Seferoglu
Multi-party computation (MPC) is promising for designing privacy-preserving machine learning algorithms at edge networks. An emerging approach is coded-MPC (CMPC), which advocates…