Neural Epistemology in Dynamical System Learning

Autor:	Pietro Barbiero, Giansalvo Cirrincione, Francesco Vaccarino, Maurizio Cirrincione, Elio Piccolo
Jazyk:	angličtina
Rok vydání:	2020
Předmět:	Artificial neural network Computer science Perspective (graphical) Poincaré recurrence theorem Epistemology Time series learning Dynamical system Bifurcation theory Feed-forward neural networks Forecasting Machine learning Simple (abstract algebra) Point (geometry)
Zdroj:	Neural Approaches to Dynamics of Signal Exchanges ISBN: 9789811389498 Neural Approaches to Dynamics of Signal Exchanges
Popis:	In the last few years, neural networks are effectively applied in different fields. However, the application of empirical-like algorithms as feed-forward neural networks is not always justified from an epistemological point of view [1]. In this work, the assumptions for the appropriate application of machine learning empirical-like algorithms to dynamical system learning are investigated from a theoretical perspective. A very simple example shows how the suggested analyses are crucial in corroborating or discrediting machine learning outcomes.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ffc48c19aeb81928ecf342ce097bb488 http://hdl.handle.net/11583/2769232 Zobrazit plný text záznamu