Presentation 2021-01-21
Unsupervised Kernel Regression with Landmarks for Large Relational Data
Shuhei Takano, Ryo Tsuno, Kazuki Noguchi, Kazuki Miyazaki, Tetsuo Furukawa,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) The aim of this work is to develop a nonlinear modeling method of large-scale relational data. For this purpose, we extended the unsupervised kernel regression for relational data. Furthermore, we made the sparse approximation by introducing landmark points into the latent spaces. As a result, we achieved a linear computational order to the data size.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Relational data analysis / Interactive Visualization / Rarge data / Visual Analytics
Paper # NC2020-32
Date of Issue 2021-01-14 (NC)

Conference Information
Committee NC / NLP
Conference Date 2021/1/21(2days)
Place (in Japanese) (See Japanese page)
Place (in English) Online
Topics (in Japanese) (See Japanese page)
Topics (in English) NC,NLP
Chair Kazuyuki Samejima(Tamagawa Univ) / Kiyohisa Natsume(Kyushu Inst. of Tech.)
Vice Chair Rieko Osu(Waseda Univ.) / Takuji Kosaka(Chukyo Univ.)
Secretary Rieko Osu(NTT) / Takuji Kosaka(ATR)
Assistant Ken Takiyama(TUAT) / Nobuhiko Wagatsuma(Toho Univ.) / Toshikaza Samura(Yamaguchi Univ.) / Hideyuki Kato(Oita Univ.)

Paper Information
Registration To Technical Committee on Neurocomputing / Technical Committee on Nonlinear Problems
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Unsupervised Kernel Regression with Landmarks for Large Relational Data
Sub Title (in English) Toward Visual Analytics Method for Complex Relational Data
Keyword(1) Relational data analysis
Keyword(2) Interactive Visualization
Keyword(3) Rarge data
Keyword(4) Visual Analytics
1st Author's Name Shuhei Takano
1st Author's Affiliation Kyushu Institute of Technology(KIT)
2nd Author's Name Ryo Tsuno
2nd Author's Affiliation Kyushu Institute of Technology(KIT)
3rd Author's Name Kazuki Noguchi
3rd Author's Affiliation Kyushu Institute of Technology(KIT)
4th Author's Name Kazuki Miyazaki
4th Author's Affiliation Kyushu Institute of Technology(KIT)
5th Author's Name Tetsuo Furukawa
5th Author's Affiliation Kyushu Institute of Technology(KIT)
Date 2021-01-21
Paper # NC2020-32
Volume (vol) vol.120
Number (no) NC-331
Page pp.pp.1-6(NC),
#Pages 6
Date of Issue 2021-01-14 (NC)