<ul><li>Federated learning leverages edge computing on client devices to optimize models while maintaining user privacy.</li><li>Latent noise in local datasets poses a challenge in federated learning due to factors like limited measurement capabilities or human errors.</li><li>To address this challenge, the proposal involves using stochastic neural networks as local models within the federated learning framework.</li><li>The approach, known as Federated Stochastic Neural Networks, aims to estimate underlying states of data and quantify latent noise, with numerical experiments demonstrating its effectiveness.</li></ul>

Federated Learning on Stochastic Neural Networks

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