Fiche publication
Date publication
juillet 2014
Journal
Neural networks : the official journal of the International Neural Network Society
Auteurs
Membres identifiés du Cancéropôle Est :
Dr LARGER Laurent
,
Mme HENRIQUES Julie
Tous les auteurs :
Grigoryeva L, Henriques J, Larger L, Ortega JP
Lien Pubmed
Résumé
Reservoir computing is a recently introduced machine learning paradigm that has already shown excellent performances in the processing of empirical data. We study a particular kind of reservoir computers called time-delay reservoirs that are constructed out of the sampling of the solution of a time-delay differential equation and show their good performance in the forecasting of the conditional covariances associated to multivariate discrete-time nonlinear stochastic processes of VEC-GARCH type as well as in the prediction of factual daily market realized volatilities computed with intraday quotes, using as training input daily log-return series of moderate size. We tackle some problems associated to the lack of task-universality for individually operating reservoirs and propose a solution based on the use of parallel arrays of time-delay reservoirs.
Mots clés
Artificial Intelligence, Computer Communication Networks, instrumentation, Computers, Data Interpretation, Statistical, Forecasting, methods, Humans, Neural Networks (Computer), Nonlinear Dynamics, Stochastic Processes, Time Factors
Référence
Neural Netw. 2014 Jul;55:59-71
