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All Technical Committee Conferences (Searched in: All Years)
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Search Results: Conference Papers |
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 |
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