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Distributed Perceptron under Bounded Staleness, Partial Participation, and Noisy Communication

We study a semi-asynchronous client-server perceptron trained via iterative parameter mixing (IPM-style averaging): clients run local perceptron updates and a server forms a global model by aggregating the updates…

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Distributed Perceptron under Bounded Staleness, Partial Participation, and Noisy Communication

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We study a semi-asynchronous client-server perceptron trained via iterative parameter mixing (IPM-style averaging): clients run local perceptron updates and a server forms a global model by aggregating the updates…

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