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Collaborative Learning with Shared Linear Representations: Statistical Rates and Optimal Algorithms
In this paper, we identify the optimal statistical rate when clients share a common low-dimensional linear representation.
Understanding Generalization of Federated Learning via Stability: Heterogeneity Matters
While the existing literature has studied extensively the generalization performances of centralized machine learning algorithms, similar analysis in the federated settings is either absent or with very restrictive assumptions on the loss functions.
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