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Adapting the Learning Rate of the Learning Rate in Hypergra..:
, In:
2020 Joint 11th International Conference on Soft Computing and Intelligent Systems and 21st International Symposium on Advanced Intelligent Systems (SCIS-ISIS)
,
Itakura, Kazuma
;
Atarashi, Kyohei
;
Oyama, Satoshi
. - p. 1-6 , 2020
Link:
https://doi.org/10.1109/SCISISIS50064.2020.9322765
RT T1 <cTitle>2020 Joint 11th International Conference on Soft Computing and Intelligent Systems and 21st International Symposium on Advanced Intelligent Systems (SCIS-ISIS)</cTitle>: T1 <Title>Adapting the Learning Rate of the Learning Rate in Hypergradient Descent</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-9322765&Exemplar=1&LAN=DE A1 Itakura, Kazuma A1 Atarashi, Kyohei A1 Oyama, Satoshi A1 Kurihara, Masahito YR 2020 K1 Training K1 Mathematical model K1 Optimization methods K1 Machine learning K1 Memory management K1 Stochastic processes K1 Information science K1 optimization K1 hypergradient descent K1 adjusting learning rate SP 1 OP 6 LK http://dx.doi.org/https://doi.org/10.1109/SCISISIS50064.2020.9322765 DO https://doi.org/10.1109/SCISISIS50064.2020.9322765 SF ELIB - SuUB Bremen
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