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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 |
2021-03-02 10:50 |
Online |
Online |
Kernel tensor decomposition based unsupervised feature extraction
-- Applications to bioinformatics -- Y-h. Taguchi (Chuo Univ.) IBISML2020-36 |
A lot of research has been done on the so-called textit{large p small n} problem, where the number of samples is small c... [more] |
IBISML2020-36 pp.16-23 |
IBISML |
2020-01-09 16:45 |
Tokyo |
ISM |
Application of tensor decomposition based unsupervised feature extraction to single cell RNA-seq analysis Y-h. Taguchi (Chuo Univ.) IBISML2019-26 |
Cannonical correlation analysis (CCA) is known to integrate two matrices, each of which have elements, $x_{ij} in mathbb... [more] |
IBISML2019-26 pp.55-59 |
IBISML |
2018-11-05 15:10 |
Hokkaido |
Hokkaido Citizens Activites Center (Kaderu 2.7) |
[Poster Presentation]
Tensor decomposition based unsupervised feature extraction applied to bioinformatics Y-h. Taguchi (Chuo Univ.) IBISML2018-90 |
Although supervised and reinforcement learning including deap learning performs excellent achievements, it is not applic... [more] |
IBISML2018-90 pp.345-352 |
IBISML |
2016-11-16 15:00 |
Kyoto |
Kyoto Univ. |
[Poster Presentation]
Principal Component Analysis based unsupervised Feature Extraction applied to Bioinformatics Y-h. Taguchi (Chuo Univ.) IBISML2016-47 |
Recently, numerous researches were performed for the machine/statisitical learning. Among those, deep learning is especi... [more] |
IBISML2016-47 pp.17-24 |
NC, IPSJ-BIO, IBISML, IPSJ-MPS (Joint) [detail] |
2015-06-23 09:30 |
Okinawa |
Okinawa Institute of Science and Technology |
Principal component analysis-based unsupervised feature extraction applied to in silico drug discovery for posttraumatic stress disorder-mediated heart disease Y-h. Taguchi, Mitsuo Iwadate, Hideaki Umeyama (Chuo Univ) IBISML2015-1 |
Background Feature extraction (FE) is difficult, particularly if there are more features than samples, as small
sample ... [more] |
IBISML2015-1 pp.1-8 |
IBISML |
2014-11-17 17:00 |
Aichi |
Nagoya Univ. |
[Poster Presentation]
Heuristic principal component analysis based unsupervised feature extraction and its application to bioinformatics Y-h. Taguchi (Chuo Univ) IBISML2014-46 |
: Feature extraction (FE) is a difficult task when the number of features is much
larger than the number of samples, a... [more] |
IBISML2014-46 pp.87-94 |
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