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Paper Abstract and Keywords
Presentation 2023-02-21 11:45
A Note on Improvement of Supervised Latent Variable Model with Graph-Encoded Class Information
Koshi Watanabe, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.)
Abstract (in Japanese) (See Japanese page) 
(in English) Supervised latent variable models aim to estimate a manifold from original data and supervised information, such as class labels. Previous approaches assumed a generation process from latent variables to supervised information. However, this assumption restricts the dimensionality of the latent space and the availability of supervised information. In this study, we utilize supervised information with graph expression and develop a method to estimate data manifold with the graph encode supervision. With this approach, we can address the previous limitations and confirm the effectiveness of the novelty through experiments.
Keyword (in Japanese) (See Japanese page) 
(in English) Latent variable model / Gaussian process / kernel method / graph / / / /  
Reference Info. IEICE Tech. Rep.
Paper #  
Date of Issue  
ISSN Online edition: ISSN 2432-6380
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Conference Information
Committee IE ITS ITE-MMS ITE-ME ITE-AIT  
Conference Date 2023-02-21 - 2023-02-22 
Place (in Japanese) (See Japanese page) 
Place (in English) Hokkaido Univ. 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Image Processing, etc. 
Paper Information
Registration To ITE-ME 
Conference Code 2023-02-MMS-ME-AIT-IE-ITS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Note on Improvement of Supervised Latent Variable Model with Graph-Encoded Class Information 
Sub Title (in English)  
Keyword(1) Latent variable model  
Keyword(2) Gaussian process  
Keyword(3) kernel method  
Keyword(4) graph  
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1st Author's Name Koshi Watanabe  
1st Author's Affiliation Hokkaido University (Hokkaido Univ.)
2nd Author's Name Keisuke Maeda  
2nd Author's Affiliation Hokkaido University (Hokkaido Univ.)
3rd Author's Name Takahiro Ogawa  
3rd Author's Affiliation Hokkaido University (Hokkaido Univ.)
4th Author's Name Miki Haseyama  
4th Author's Affiliation Hokkaido University (Hokkaido Univ.)
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Speaker Author-1 
Date Time 2023-02-21 11:45:00 
Presentation Time 15 minutes 
Registration for ITE-ME 
Paper #  
Volume (vol) vol.122 
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