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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 11 of 11  /   
Committee Date Time Place Paper Title / Authors Abstract Paper #
IBISML 2018-11-05
15:10
Hokkaido Hokkaido Citizens Activites Center (Kaderu 2.7) [Poster Presentation] Learning Restricted Boltzmann Machine via the Adaptive Thouless-Anderson-Palmer Mean-Field Approximation
Chako Takahashi (Tohoku Univ.), Muneki Yasuda (Yamagata Univ.), Kazuyuki Tanaka (Tohoku Univ.) IBISML2018-58
(Advance abstract in Japanese is available) [more] IBISML2018-58
pp.105-110
SP, IPSJ-SLP
(Joint)
2013-07-26
14:20
Miyagi Soho (togatta spa) [Invited Talk] An Introduction to Deep Learning -- Restricted Boltzmann Machine and Pre-Training --
Muneki Yasuda (Yamagata Univ.) SP2013-60
Deep learnings are learnings on multi-layered learning models.
Deep learnings have achieved astounding success in the f... [more]
SP2013-60
pp.45-49
MBE, NC
(Joint)
2012-11-17
13:30
Miyagi Tohoku University Composite likelihood estimation for bipartite Boltzmann machines
Takashi Asari, Muneki Yasuda, Yuji Waizumi, Kazuyuki Tanaka (Tohoku Univ.) NC2012-68
The recent development of information technology has enabled us to obtain and to storage huge information data.
Because... [more]
NC2012-68
pp.39-44
MBE, NC
(Joint)
2012-11-17
14:55
Miyagi Tohoku University Design of probabilistic image inpainting filters using Gaussian graphial models
Tomotaka Kitagawa, Muneki Yasuda, Kazuyuki Tanaka (Tohoku Univ.) NC2012-71
A probabilistic image inpainting lter is an image processing lter that reconstructs lost or deteriorated pixels of ima... [more] NC2012-71
pp.57-62
MBE, NC
(Joint)
2012-03-16
13:20
Tokyo Tamagawa University Item Response Theory with Correlations among Items
Muneki Yasuda, Kazuyuki Tanaka (Tohoku Univ.) NC2011-187
Item response theory (IRT) is a recent test theory which has been developed in mainly psychology and social science.
A ... [more]
NC2011-187
pp.387-391
IBISML 2011-11-09
15:45
Nara Nara Womens Univ. Gaussian FoE model with correlations among color components
Ryuta Murayama, Muneki Yasuda, Yuji Waizumi, Kazuyuki Tanaka (Tohoku Univ.) IBISML2011-58
Color images consist of some color components such as RGB, YCbCr. They have been often treated independently in usual im... [more] IBISML2011-58
pp.105-111
IBISML 2010-11-04
15:00
Tokyo IIS, Univ. of Tokyo [Poster Presentation] Advanced Susceptibility Propagation
Muneki Yasuda, Kazuyuki Tanaka (Tohoku Univ.) IBISML2010-67
Inferences in Markov random fields are ones of the most important problems in information science.
Susceptibility prop... [more]
IBISML2010-67
pp.59-63
IBISML 2010-11-05
15:30
Tokyo IIS, Univ. of Tokyo [Poster Presentation] Statistical Mechanical Informatics for Portfolio Optimization Problems
Takashi Shinzato (Akita Pref. Univ.), Muneki Yasuda (Tohoku Univ.) IBISML2010-94
(Advance abstract in Japanese is available) [more] IBISML2010-94
pp.257-263
NC, MBE
(Joint)
2009-03-12
14:15
Tokyo Tamagawa Univ. Learning algorithm in Boltzmann machines using the belief propagation algorithm
Junya Tannai, Muneki Yasuda, Kazuyuki Tanaka (Tohoku Univ.) NC2008-144
Boltzmann machines are stochastic neural networks defined on undirected graphs and are expected to be learning machines ... [more] NC2008-144
pp.243-248
NC, MBE
(Joint)
2008-03-12
10:00
Tokyo Tamagawa Univ Gaussian Graphical Model on Scale-Free Network
Takafumi Usui, Muneki Yasuda, Kazuyuki Tanaka (Tohoku Univ.) NC2007-112
We consider probabilistic inferences formulated by using Gaussian graphical models on scale free networks.
We can deriv... [more]
NC2007-112
pp.1-5
NC, MBE
(Joint)
2008-03-12
13:30
Tokyo Tamagawa Univ Image Processing by using the EM algorithm and the belief propagation
Kei Inoue, Muneki Yasuda, Kazuyuki Tanaka (Tohoku Univ.) NC2007-118
Markov random fields in image processing includehyperparameters to estimate from given data. We introduce a method to es... [more] NC2007-118
pp.37-42
 Results 1 - 11 of 11  /   
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