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Library to simulate a distributed learning scenario, with clusters of users that train models minimizing a local cost function, and a server that wants to minimize a global cost function. The aim of the project is to study the tradeoff between local and global accuracy.
[ICLR 2023] "Combating Exacerbated Heterogeneity for Robust Models in Federated Learning"