Search Results for author:
Found 1 papers, 0 papers with code
Optimal Privacy Preserving for Federated Learning in Mobile Edge Computing
This theoretical bound is decomposed into two components, including the variance of the global gradient and the quadratic bias that can be minimized by optimizing the communication resources, and quantization/noise parameters.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
