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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 6 of 6  /   
Committee Date Time Place Paper Title / Authors Abstract Paper #
NC, MBE 2019-12-06
17:20
Aichi Toyohashi Tech Regularization Term of WRH Type Used with Moore-Penrose Inverse for Optimizing Neural Networks
Yoshifusa Ito (FHU), Hiroyuki Izumi (AGU), Cidambi Srinivasan (UK) MBE2019-60 NC2019-51
Weigend et al. proposed an algorithm for optimizing neural networks, which suppressed the notorious over- tting. They at... [more] MBE2019-60 NC2019-51
pp.89-94
NC, MBE
(Joint)
2018-12-15
14:25
Aichi Nagoya Institute of Technology Approximation of Bayesian Discriminant Functions by Neural Networks with Weight Elimination
Yoshifusa Ito (FHU), Hiroyuki Izumi (AGU), Cidambi Srinivasan (UK) NC2018-34
 [more] NC2018-34
pp.35-40
MBE, NC
(Joint)
2017-12-16
10:30
Aichi Nagoya University Application of ELM for Approximating Bayesian Discriminant Functions
Yoshifusa Ito (FHU), Hiroyuki Izumi (AGU), Cidambi Srinivasan (UK) NC2017-40
 [more] NC2017-40
pp.1-6
NC, MBE
(Joint)
2012-12-12
17:30
Aichi Toyohashi University of Technology Learning of Mahalanobis discriminant functions by a neural network -- For non-normally distributed signals --
Hiroyuki Izumi (AGU), Yoshifusa Ito (AMU), Cidambi Srinivasan (UKY) NC2012-90
 [more] NC2012-90
pp.79-84
NC, MBE
(Joint)
2008-03-12
16:50
Tokyo Tamagawa Univ Conversion of inner parameters to outer parameters
Yoshifusa Ito, Hiroyuki Izumi (Aichi-Gakuin Univ.) NC2007-127
To overcome difficultites in learning of $a$ three-layer nural network, construction of $a$ network with hidden-layer un... [more] NC2007-127
pp.91-96
NC 2007-06-15
13:25
Okinawa OIST Seaside House Learning of Neural Networks with Dichotomic Random Teacher Signals
Yoshifusa Ito (AGU), Cidambi Srinivasan (UKY), Hiroyuki Izumi (AGU) NC2007-21
Learning with dichotomic random teacher signals is a hard task for neural networks, because the learning cannot be compl... [more] NC2007-21
pp.75-80
 Results 1 - 6 of 6  /   
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