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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 49  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
NC, MBE
(Joint)
2021-03-03
16:00
Online Online What is the true objective of multi-task manifold modeling? -- Comparison of maximum likelihood and optimal transport approaches --
Ryo Tsuno, Hideaki Ishibashi, Tetsuo Furukawa (KIT) NC2020-52
 [more] NC2020-52
pp.53-58
NC, NLP
(Joint)
2021-01-21
11:15
Online Online Unsupervised Kernel Regression with Landmarks for Large Relational Data -- Toward Visual Analytics Method for Complex Relational Data --
Shuhei Takano, Ryo Tsuno, Kazuki Noguchi, Kazuki Miyazaki, Tetsuo Furukawa (KIT) NC2020-32
The aim of this work is to develop a nonlinear modeling method of large-scale relational data. For this purpose, we exte... [more] NC2020-32
pp.1-6
NLP, NC
(Joint)
2020-01-24
09:30
Okinawa Miyakojima Marine Terminal Visualization of document-word relation by modeling their joint probability on latent spaces
Takuro Ishida, Keisuke Yoneda, Hajime Hatano, Tetsuo Furukawa (Kyutech) NC2019-60
The aim of this work is to visualize the relation of documents and words by embedding them to the product space of laten... [more] NC2019-60
pp.7-12
NLP, NC
(Joint)
2020-01-24
09:50
Okinawa Miyakojima Marine Terminal [Short Paper] Visualization of children's interactions in the group discussion by Tensor SOM
Keisuke Kusumoto, Keiichi Horio, Tetsuo Furukawa (KIT) NC2019-61
Our aim is to visualize the relationship between children and their social developmental states in a kindergarten. In th... [more] NC2019-61
pp.13-16
NLP, NC
(Joint)
2020-01-24
10:10
Okinawa Miyakojima Marine Terminal Optimal Transport based Autoencoder for class and style Disentanglement
Florian Tambon, Tetsuo Furukawa (Kyutech) NC2019-62
The Sinkhorn autoencoder is a novel generative model using optimal transport to model the aggregated posterior from samp... [more] NC2019-62
pp.17-22
NLP, NC
(Joint)
2020-01-24
10:30
Okinawa Miyakojima Marine Terminal Visualization of Relational data by Embedding to Direct Product Space
Kazuki Miyazaki, Ryuji Watanabe, Tetsuo Furukawa (Kyutech) NC2019-63
The aim of this work is to develop a modeling method of relational data. Relational data is a dataset observed obtained ... [more] NC2019-63
pp.23-26
NLP, NC
(Joint)
2020-01-24
10:50
Okinawa Miyakojima Marine Terminal Visualization tool for basketball team performance by multi-level SOM
Kanta Senoura, Hideaki Ishibashi, Tetsuo Furukawa (KIT) NC2019-64
The purpose of this work is to develop a method to visualize the relation between the team performance and the member co... [more] NC2019-64
pp.27-31
NLP, NC
(Joint)
2020-01-25
14:30
Okinawa Miyakojima Marine Terminal Expert User-Item Modeling Each Topics Based on Tensor SOM and Latent Dirichlet Allocation
Tatsuya Kanatsu, Tetsuo Furukawa, Kaori Yoshida (Kyutech) NC2019-74
User-item modeling is the foundation of recommendation systems. In this paper, we propose a method of building a set of ... [more] NC2019-74
pp.83-88
HCS 2019-03-07
13:00
Hokkaido Hokusei Gakuen Univ. Consideration of Behavior Modification at Member Change in Behavior Analysis of Children during Discussion
Ryo Fukuda, Keiichi Horio, Tetsuo Furukawa (Kyushu Inst. of Tech.), Takashi Omori (Tamagawa Univ.) HCS2018-67
 [more] HCS2018-67
pp.1-6
SIS 2018-12-06
14:50
Yamaguchi Hagi Civic Center Multi-View Analysis for Conditions of Players in Team Sports
Haruka Kondo (Kyushu Inst. of Tech.), Masaki Iwasaaki (BraTech Co., Ltd.), Hirohisa Isogai (BAS Lab.), Tetsuo Furukawa, Keiichi Horio (Kyushu Inst. of Tech.) SIS2018-26
In this study, an estimation of an optimal psychological state for each player is achieved to improve the performances o... [more] SIS2018-26
pp.25-29
HCS, HIP, HI-SIGCE [detail] 2018-05-22
09:30
Okinawa Okinawa Industry Support Center Clustering of Children Based on Behavior Analysis and Consideration of Individuality Analysis
Keiichi Horio, Yuji Watanabe, Tetsuo Furukawa (Kyushu Inst. of Tech.), Takashi Omori (Tamagawa Univ.) HCS2018-13 HIP2018-13
In this study, features such as speech, line of sight, response, posture, etc. were extracted from moving images taken b... [more] HCS2018-13 HIP2018-13
pp.101-106
MBE, NC, NLP
(Joint)
2018-01-26
15:25
Fukuoka Kyushu Institute of Technology A Multi-task Learning Algorithm using SOM
Kazushi Higa, Tetsuo Furukawa (Kyutech) NC2017-55
 [more] NC2017-55
pp.29-33
MBE, NC
(Joint)
2017-11-24
16:50
Miyagi Tohoku University NC2017-32 Continuous latent variable model is a category of dimension reduction methods, which estimates low dimensional latent va... [more] NC2017-32
pp.29-34
IBISML 2017-11-09
13:00
Tokyo Univ. of Tokyo Evaluation of KL-divergence between Gaussian process posteriors by finite dimensional normal distributions
Hideaki Ishibashi, Tetsuo Furukawa (Kyutech), Shotaro Akaho (AIST) IBISML2017-55
 [more] IBISML2017-55
pp.155-160
NC, IPSJ-BIO, IBISML, IPSJ-MPS [detail] 2017-06-23
17:40
Okinawa Okinawa Institute of Science and Technology Kansei analysis of landscape images by Tensor SOM -- Simultaneous analysis of evaluators, subjects, and evaluation words --
Kyouhei Itonaga (Kyutech), Tohru Iwasaki (Colorcle), Kaori Yoshida, Tetsuo Furukawa (Kyutech) NC2017-12
In the field of Kansei evaluation, it is investigated and analyzed by using evaluation words with various subjects and o... [more] NC2017-12
pp.45-50
MBE, NC
(Joint)
2017-05-26
13:00
Toyama Toyama Prefectural Univ. Nonlinear Canonical Correlation Analysis of Multi-view Data by Metric Learning between SOMs
Keisuke Yoneda (Kyutech), Kirihiro Nakano (Kuraray), Keiichi Horio, Tetsuo Furukawa (Kyutech) NC2017-1
 [more] NC2017-1
pp.1-6
NC, NLP
(Joint)
2017-01-26
16:50
Fukuoka Kitakyushu Foundation for the Advanement of Ind. Sci. and Tech. intrinsic viewpoint estimation of multiple survey dataset
Hideaki Ishibashi, Ryota Shinriki, Hirohisa Isogai, Tetsuo Furukawa (Kyutech) NC2016-54
In the field of computer vision, 3D reconstruction method which estimates the three-dimensional shape of an object captu... [more] NC2016-54
pp.37-41
NC, NLP
(Joint)
2017-01-27
15:15
Fukuoka Kitakyushu Foundation for the Advanement of Ind. Sci. and Tech. Complex tensor data analysis by tensor SOM network and information propagation in the network
Yuki Toshima, Tetsuo Furukawa (kyutech) NC2016-62
Multimode data (relational data) is generally expressed as a tensor. In the analysis of tensor data, not only analysis o... [more] NC2016-62
pp.83-88
NC, NLP
(Joint)
2016-01-29
16:40
Fukuoka Kyushu Institute of Technology Simultaneous visualization of topics and human relations from e-mail dataset by Tensor SOM.
Hajime Hatano, Tetsuo Furukawa (KyuTech) NC2015-68
 [more] NC2015-68
pp.61-66
NC, IPSJ-BIO, IBISML, IPSJ-MPS
(Joint) [detail]
2015-06-23
11:35
Okinawa Okinawa Institute of Science and Technology Multiple Latent Space GTM for Visualization of Tensorial Data
Kazushi Higa, Tetsuo Furukawa (Kyutech) IBISML2015-6
The generative topographic map (GTM) is a continuous latent space model, which enables to visualize a high-dimensional d... [more] IBISML2015-6
pp.33-38
 Results 1 - 20 of 49  /  [Next]  
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