Echo State Queueing Networks: a combination of Reservoir Computing and Random Neural Networks

Gerardo Rubino 1 Sebastián Basterrech 2
1 DIONYSOS - Dependability Interoperability and perfOrmance aNalYsiS Of networkS
Inria Rennes – Bretagne Atlantique , IRISA_D2 - RÉSEAUX, TÉLÉCOMMUNICATION ET SERVICES
Abstract : This paper deals with two ideas appeared during the last developing phase in Artificial Intelligence: Reservoir Computing and Random Neural Networks. Both have been very successful in many applications. We propose a new model belonging to the first class, taking the structure of the second for its dynamics. The new model is called Echo State Queuing Network. The paper positions the model in the global Machine Learning area, and provides examples of its use and performances. We show on largely used benchmarks that it is a very accurate tool, and we illustrate how it compares with standard Reservoir
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Probability in the Engineering and Informational Sciences, Cambridge University Press (CUP), 2017, 31 (4), pp.457-476. 〈10.1017/S0269964817000110〉
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Soumis le : jeudi 14 décembre 2017 - 03:22:50
Dernière modification le : mercredi 16 mai 2018 - 11:24:13

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Gerardo Rubino, Sebastián Basterrech. Echo State Queueing Networks: a combination of Reservoir Computing and Random Neural Networks. Probability in the Engineering and Informational Sciences, Cambridge University Press (CUP), 2017, 31 (4), pp.457-476. 〈10.1017/S0269964817000110〉. 〈hal-01663499〉

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