Doubly random parallel stochastic methods for large scale learning

We consider learning problems over training sets in which both, the number of training examples and the dimension of the feature vectors, are large. To solve these problems we propose the random parallel stochastic algorithm (RAPSA). We call the algorithm random parallel because it utilizes multiple...

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Bibliographic Details

Published in:	Proceedings of the American Control Conference pp. 4847 - 4852
Main Authors:	Mokhtari, Aryan, Koppel, Alec, Ribeiro, Alejandro
Format:	Conference Proceeding Journal Article
Language:	English
Published:	American Automatic Control Council (AACC) 01.07.2016
Subjects:	Algorithms Convergence Learning Linear programming Mathematical analysis Optimization Parallel processing Processors Program processors Radio frequency Stochasticity Training Vectors (mathematics)
ISSN:	2378-5861
Online Access:	Get full text
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