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Found 3 papers, 1 papers with code
Towards Model-Agnostic Federated Learning over Networks
Our method is an instance of empirical risk minimization, with the regularization term derived from the network structure of data.
flow-based clustering and spectral clustering: a comparison
What sets our approach apart from spectral clustering is that we do not use the eigenvectors of a graph Laplacian to construct the feature vectors.
Federated Learning From Big Data Over Networks
We obtain a distributed federated learning algorithm via a message passing implementation of this primal-dual method.
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