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...
| Huvudupphovsmän: | , , |
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| Materialtyp: | Conference item |
| Språk: | English |
| Publicerad: |
Proceedings of Machine Learning Research
2020
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