Decentralised learning with distributed gradient descent and random features

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...

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Bibliografische gegevens
Hoofdauteurs: Richards, D, Rebeschini, P, Rosasco, L
Formaat: Conference item
Taal:English
Gepubliceerd in: Proceedings of Machine Learning Research 2020