An adaptation of the PARAFAC-ALS algorithm is implemented with the purpose of providing accurate and efficient estimates of CANDECOMP/PARAFAC parameters without being influenced by data characteristics and model specifications. This is a dual-optimization procedure in which values are first estimated by SWATLD and then refined through standard ALS steps. The use of an additional optimization phase is suggested with the purpose of canceling out specific ALS inefficiencies such as slow convergence and occurrence of over-factoring degeneracies. A complex simulation study is then implemented in order to identify the most adequate transition point between the stages of the proposed methodology and to show its advantages with respect to standard ALS.

Improving PARAFAC-ALS estimates with a double optimization procedure / Simonacci, V; Gallo, M. - In: CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS. - ISSN 0169-7439. - 192:(2019), p. 103822. [10.1016/j.chemolab.2019.103822]

Improving PARAFAC-ALS estimates with a double optimization procedure

Simonacci V;
2019

Abstract

An adaptation of the PARAFAC-ALS algorithm is implemented with the purpose of providing accurate and efficient estimates of CANDECOMP/PARAFAC parameters without being influenced by data characteristics and model specifications. This is a dual-optimization procedure in which values are first estimated by SWATLD and then refined through standard ALS steps. The use of an additional optimization phase is suggested with the purpose of canceling out specific ALS inefficiencies such as slow convergence and occurrence of over-factoring degeneracies. A complex simulation study is then implemented in order to identify the most adequate transition point between the stages of the proposed methodology and to show its advantages with respect to standard ALS.
2019
Improving PARAFAC-ALS estimates with a double optimization procedure / Simonacci, V; Gallo, M. - In: CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS. - ISSN 0169-7439. - 192:(2019), p. 103822. [10.1016/j.chemolab.2019.103822]
File in questo prodotto:
File Dimensione Formato  
1-s2.0-S0169743918305896-main.pdf

non disponibili

Dimensione 1.51 MB
Formato Adobe PDF
1.51 MB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/872752
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 3
  • ???jsp.display-item.citation.isi??? 3
social impact