Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
NC, MBE (Joint) |
2021-03-03 16:00 |
Online |
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 (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 (Okinawa) |
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 (Okinawa) |
[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 (Okinawa) |
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 (Okinawa) |
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 (Okinawa) |
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 (Okinawa) |
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. (Hokkaido) |
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 (Yamaguchi) |
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-SIGCOASTER [detail] |
2018-05-22 09:30 |
Okinawa |
Okinawa Industry Support Center (Okinawa) |
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 (Fukuoka) |
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 (Miyagi) |
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 (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 (Okinawa) |
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. (Toyama) |
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. (Fukuoka) |
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. (Fukuoka) |
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 (Fukuoka) |
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 (Okinawa) |
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 |