Corpus ID: 220281086

# Decentralised Learning with Random Features and Distributed Gradient Descent

@article{Richards2020DecentralisedLW,
title={Decentralised Learning with Random Features and Distributed Gradient Descent},
author={Dominic Richards and Patrick Rebeschini and Lorenzo Rosasco},
journal={ArXiv},
year={2020},
volume={abs/2007.00360}
}
• Published 1 July 2020
• Computer Science, Mathematics
• ArXiv
We investigate the generalisation performance of Distributed Gradient Descent with Implicit Regularisation and Random Features in the homogenous setting where a network of agents are given data sampled independently from the same unknown distribution. Along with reducing the memory footprint, Random Features are particularly convenient in this setting as they provide a common parameterisation across agents that allows to overcome previous difficulties in implementing Decentralised Kernel… Expand
4 Citations

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