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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
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Committee Date Time Place Paper Title / Authors Abstract Paper #
IBISML 2022-03-09
14:55
Online Online Infinite SCAN: Joint Estimation of Changes and the Number of Word Senses with Gaussian Markov Random Fields
Seiichi Inoue, Mamoru Komachi (TMU), Toshinobu Ogiso (NINJAL), Hiroya Takamura (AIST), Daichi Mochihashi (ISM) IBISML2021-47
In this study, we propose a hierarchical Bayesian model that can automatically estimate the number of senses for each wo... [more] IBISML2021-47
pp.61-68
IBISML 2018-11-05
15:10
Hokkaido Hokkaido Citizens Activites Center (Kaderu 2.7) [Poster Presentation] Lattice Model Selection of Gaussian Markov Random Field
Hirosato Ito, Hirotaka Sakamoto, Shun Katakami, Masato Okada (Univ. Tokyo) IBISML2018-69
Recently, many observed images have been obtained in various natural scientific fields. It is very important issue to e... [more] IBISML2018-69
pp.191-196
IBISML 2017-11-10
13:00
Tokyo Univ. of Tokyo Approximated hyperparameter distribution estimation using Gaussian process and Bayesian optimization
Shun Katakami, Hirotaka Sakamoto, Masato Okada (UTokyo) IBISML2017-81
In order to reduce the computational cost of Bayesian inference, we propose a method to estimate the Bayesian posterior ... [more] IBISML2017-81
pp.333-338
IBISML 2011-11-10
15:45
Nara Nara Womens Univ. Image Restoration and Segmentation Based on Compound Gaussian Markov Random Field Extended as Mixture Model
Takayuki Katsuki, Masato Inoue (Waseda Univ.) IBISML2011-75
This report proposes an accurate image restoration and segmentation using a new image model. The model is a compound Gau... [more] IBISML2011-75
pp.223-230
NC, MBE
(Joint)
2011-03-09
11:05
Tokyo Tamagawa University Image restoration for computed tomography image with Bayesian approach
Junta Ueki, Hayaru Shouno (UEC) NC2010-189
When a doctor diagnose patient,a doctor use a computed tomography image.When we get computed tomography image,we expect ... [more] NC2010-189
pp.367-372
 Results 1 - 5 of 5  /   
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