DRASiW is an extension of the WiSARD Weightless NN model with the capability of storing the frequencies of seen patterns during the training stage in an internal data structure called "mental image" (MI). Due to these capability, in previous work it was demonstrated how to reversely process MIs in order to generate synthetic prototypes from training samples. In this paper we show how DRASiW-like systems are able to transfer memory between different architectures while preserving the same functionalities.

Memory transfer in DRASiW-like systems

De Gregorio Massimo;Giordano Maurizio
2015

Abstract

DRASiW is an extension of the WiSARD Weightless NN model with the capability of storing the frequencies of seen patterns during the training stage in an internal data structure called "mental image" (MI). Due to these capability, in previous work it was demonstrated how to reversely process MIs in order to generate synthetic prototypes from training samples. In this paper we show how DRASiW-like systems are able to transfer memory between different architectures while preserving the same functionalities.
2015
Istituto di Calcolo e Reti ad Alte Prestazioni - ICAR
Istituto di Scienze Applicate e Sistemi Intelligenti "Eduardo Caianiello" - ISASI
Inglese
Proc. 24th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning
European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning
25
30
9782875870148
http://www.scopus.com/record/display.url?eid=2-s2.0-84961785327&origin=inward
22-24 April 2015
Bruges, Belgio
artificial neural networks; machine learning
weightless neural networks
2
none
De Gregorio, Massimo; Giordano, Maurizio
273
info:eu-repo/semantics/conferenceObject
04 Contributo in convegno::04.01 Contributo in Atti di convegno
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/324198
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