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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 9 of 9  /   
Committee Date Time Place Paper Title / Authors Abstract Paper #
NC, MBE
(Joint)
2014-03-17
15:00
Tokyo Tamagawa University Visualization using Supervised Generative Topographic Mapping
Nobuhiko Yamaguchi (Saga Univ.) NC2013-97
Generative Topographic Mapping (GTM) is a nonlinear latent variable model introduced by Bishop et al. as a data visualiz... [more] NC2013-97
pp.53-58
MBE, NC
(Joint)
2013-03-15
10:15
Tokyo Tamagawa University Bayesian inference for GTM using non-stationary Gaussian process
Nobuhiko Yamaguchi (Saga Univ.) NC2012-168
Generative Topographic Mapping (GTM) is a nonlinear topographically preserving mapping from latent to data space introdu... [more] NC2012-168
pp.197-202
MBE, NC
(Joint)
2012-03-15
14:35
Tokyo Tamagawa University Constructing sparse generative topographic mapping using variational Bayes
Nobuhiko Yamaguchi (Saga Univ.) NC2011-166
Generative Topographic Mapping (GTM) is a nonlinear latent variable model introduced by Bishop {\it et al.} as a data vi... [more] NC2011-166
pp.263-268
NC, MBE
(Joint)
2011-03-08
10:15
Tokyo Tamagawa University Self-organizing hidden markov models
Nobuhiko Yamaguchi (Saga Univ.) NC2010-166
The self-organizing mixture models (SOMMs) algorithm was proposed as an expectation-maximization (EM) algorithm that yie... [more] NC2010-166
pp.229-234
NC, MBE
(Joint)
2010-03-09
13:20
Tokyo Tamagawa University Self-organizing hidden markov models
Nobuhiko Yamaguchi (Saga Univ.) NC2009-104
The self-organizing mixture models (SOMMs) algorithm was proposed as an expectation-maximization (EM) algorithm that yie... [more] NC2009-104
pp.95-100
NC, MBE
(Joint)
2009-03-12
15:15
Tokyo Tamagawa Univ. Visualization of time series using GTM
Nobuhiko Yamaguchi (Saga Univ.) NC2008-135
The GTM (Generative Topographic Mapping) algorithm was proposed
as a probabilistic re-formulation of the self-organizi... [more]
NC2008-135
pp.189-194
NC 2007-11-19
14:15
Saga Saga Univ. Constructing error correcting output coding using latent variable models
Nobuhiko Yamaguchi (Saga Univ.) NC2007-70
The object of this paper is to construct a multi-class classifier by Error-Correcting Output Coding (ECOC) approach. The... [more] NC2007-70
pp.89-93
NC 2007-03-15
13:20
Tokyo Tamagawa University Constructing error correcting output coding using latent variable models
Nobuhiko Yamaguchi (Saga Univ.)
The object of this paper is to construct a multi-class classifier by Error-Correcting Output Coding (ECOC) approach. The... [more] NC2006-177
pp.141-145
NC 2006-03-16
11:25
Tokyo Tamagawa University Combining pairwise coupling classifiers using individual logistic regressions
Nobuhiko Yamaguchi (Saga univ.)
Pairwise coupling is a popular multi-class classification method that combines all combinations for each pair of classes... [more] NC2005-141
pp.97-101
 Results 1 - 9 of 9  /   
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