Asynchrounous Decentralized Learning of a Neural Network

In this work, we exploit an asynchronous computing framework namely ARock to learn a deep neural network called self-size estimating feedforward neural network (SSFN) in a decentralized scenario. Using this algorithm namely asynchronous decentralized SSFN (dSSFN), we provide the centralized equivale...

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Vydané v:	Proceedings of the ... IEEE International Conference on Acoustics, Speech and Signal Processing (1998) s. 3947 - 3951
Hlavní autori:	Liang, Xinyue, Javid, Alireza M., Skoglund, Mikael, Chatterjee, Saikat
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 01.05.2020
Predmet:	Asynchronous Communication networks convex optimization decentralized learning Feedforward neural networks neural networks Optimization Signal processing Signal processing algorithms Sparse matrices Speech processing
ISSN:	2379-190X
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