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Parametrizing GP Trees for Better Symbolic Regression Perfo..:
, In:
Proceedings of the Companion Conference on Genetic and Evolutionary Computation
,
Pietropolli, Gloria
;
Camerota Verdù, Federico Julian
;
Manzoni, Luca
. - p. 619-622 , 2023
Link:
https://dl.acm.org/doi/10.1145/3583133.3590574
RT T1 <cTitle>Proceedings of the Companion Conference on Genetic and Evolutionary Computation</cTitle>: T1 <Title>Parametrizing GP Trees for Better Symbolic Regression Performance through Gradient Descent.</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3590574&Exemplar=1&LAN=DE A1 Pietropolli, Gloria A1 Camerota Verdù, Federico Julian A1 Manzoni, Luca A1 Castelli, Mauro PB ACM YR 2023 K1 genetic programming K1 gradient descent K1 local search K1 adam K1 memetic search K1 Computing methodologies K1 Machine learning K1 Machine learning approaches K1 Bio-inspired approaches K1 Genetic programming SP 619 OP 622 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3583133.3590574 DO https://dl.acm.org/doi/10.1145/3583133.3590574 SF ELIB - SuUB Bremen
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