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Federated Classification With Low Complexity Reproducing Kernel Hilbert Space Representations

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IEEE ICASSP 2020 Virtual Conference May 2020

In federated learning, a centralized model is realized based on information received from a group of agents each collecting data. This setting has two major challenges: the agents observe data over different distributions and they have only limited capabi

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Federated Classification With Low Complexity Reproducing Kernel Hilbert Space Representations

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In federated learning, a centralized model is realized based on information received from a group of agents each collecting data. This setting has two major challenges: the agents observe data over different distributions and they have only limited capabi