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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| PRMU | 2022-12-16 16:15 |
Toyama | Toyama International Conference Center (Primary: On-site, Secondary: Online) |
On partitioning of the space of one-dimensional normal distributions based on e(m)-divergence Jun Fujiki (Fukuoka Univ.), Shotaro Akaho (AIST)  PRMU2022-54 |
Partitioning of the space of one-dimensional normal distributions based on e(m)-divergence is useful when clustering and... [more] | PRMU2022-54 pp.116-121 |
| NLP, MICT, MBE, NC (Joint) [detail] |
2022-01-23 11:20 |
Online | Online | Towards 2-class classification via e(m)-PCA Jun Fujiki (Fukuoka Univ.), Shotaro Akaho (AIST) NC2021-43 |
In many data analysis methods, observed data are treated as points in high-dimensional Euclidean space, called feature s... [more] | NC2021-43 pp.55-58 |
| IBISML | 2022-01-17 11:00 |
Online | Online | Cluster approximation in quantum Boltzmann machine based on information geometry Masaya Hoshikawa, Tomohiro Ogawa (UEC) IBISML2021-21 |
A Boltzmann Machine (BM) is a model of machine learning which consists of mutually connected probabilistic binary units... [more] |
IBISML2021-21 pp.23-28 |
| NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] | 2021-06-28 16:50 |
Online | Online | Constellation of time dependent data using information geometry Taiki Sugiura, Takuma Fuse (Recruit), Noboru Murata (Waseda Univ.) NC2021-9 IBISML2021-9 |
Constellation is an essential technique for gaining knowledge from large amounts of high-dimensional data and understand... [more] | NC2021-9 IBISML2021-9 pp.62-69 |
| IE, ITS, ITE-MMS, ITE-ME, ITE-AIT [detail] | 2021-02-19 13:45 |
Online | Online | [Special Talk]
The data science educator and mathematics
-- from graduate student in mathematics viewpoint -- Naomichi Nakajima (Hokkaido Univ.) |
At the Education and Research Center for Mathematical and Data Science, Hokkaido University (MDS center), education of t... [more] | |
| IBISML | 2020-01-09 13:50 |
Tokyo | ISM | Dimensionality reduction method for gaussian process posteriors based on information geometry Hideaki Ishibashi (Kyutech), Shotaro Akaho (AIST/RIKEN) IBISML2019-20 |
This paper proposes an extension of principal component analysis for gaussian process posteriors which is denoted by GP-... [more] | IBISML2019-20 pp.17-24 |
| SIP, EA, SP, MI (Joint) [detail] |
2018-03-19 13:40 |
Okinawa | [Short Paper]
Proposal of a spatio-temporal statistical model of generated anatomical landmarks Aoi Shinjo, Atsushi Saito (TUAT), Tetsuya Takakuwa, Shigehito Yamada (Kyoto Univ.), Hiroshi Matsuzoe, Hidekata Hontani (NITech), Akinobu Shimizu (TUAT) MI2017-77 |
(To be available after the conference date) [more] | MI2017-77 pp.41-42 |
|
| WBS, IT, ISEC | 2018-03-08 09:25 |
Tokyo | Katsusika Campas, Tokyo University of Science | Information Geometrical Study of Cluster-Model Approximation for Boltzmann Machines Kenta Toyoda, Tomohiro Ogawa (Univ. of Electro- Commu.) IT2017-104 ISEC2017-92 WBS2017-85 |
In learning algorithms for Boltzmann machines, it is necessary but very hard to calculate the expectation of units with ... [more] | IT2017-104 ISEC2017-92 WBS2017-85 pp.7-12 |
| IBISML | 2018-03-05 13:25 |
Fukuoka | Nishijin Plaza, Kyushu University | Information Geometry of Modal Linear Regression Keishi Sando (Univ. of Tsukuba), Shotaro Akaho (AIST), Noboru Murata (Waseda Univ.), Hideitsu Hino (Univ. of Tsukuba) IBISML2017-91 |
(To be available after the conference date) [more] | IBISML2017-91 pp.7-14 |
| IBISML | 2018-03-05 14:15 |
Fukuoka | Nishijin Plaza, Kyushu University | Exponential Family of Markov Kernels and Asymptotic Exponential Family of Markov Sources Jun'ichi Takeuchi (Kyushu Univ.), Hiroshi Nagaoka (UEC) IBISML2017-93 |
For parametric models of Markov sources, we prove that the notion of asymptotic exponential family is equivalent to the ... [more] | IBISML2017-93 pp.21-25 |
| 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 |
| PRMU, BioX | 2017-03-20 10:25 |
Aichi | Heisemberg group and exponential family
-- From the point of view of information geometry -- Akira Tokimatsu, Masaru Tanaka (Fukuoka Univ.) BioX2016-34 PRMU2016-197 |
(To be available after the conference date) [more] | BioX2016-34 PRMU2016-197 pp.7-10 |
|
| QIT (2nd) |
2016-11-24 13:00 |
Ibaraki | KEK Kobayashi-hall | [Poster Presentation]
Data processing for qubit state tomography: An information geometric approach Koichi Yamagata (Chuo Univ), Akio Fujiwara (Osaka Univ) |
A statistically feasible data post-processing method for the conventional qubit state tomography is studied from an in... [more] |
|
| IBISML | 2016-11-17 17:00 |
Kyoto | Kyoto Univ. | [Poster Presentation]
How to make Tsallis entropy become an additive entropy Masaru Tanaka (Fukuoka Univ.) IBISML2016-99 |
$tau$-information geometry, that is a new formulation of information geometry, is given by extending a translation opera... [more] | IBISML2016-99 pp.381-386 |
| IBISML | 2015-11-26 15:00 |
Ibaraki | Epochal Tsukuba | [Poster Presentation]
Non-parametric e-mixture Estimation Ken Takano (Waseda Univ.), Hideitsu Hino (Univ. of Tsukuba), Shotaro Akaho (AIST), Noboru Murata (Waseda Univ.) IBISML2015-59 |
Mixture modeling is one of the simplest ways to represent complicated probability density functions, and to integrate in... [more] | IBISML2015-59 pp.45-52 |
| IBISML | 2015-11-26 15:00 |
Ibaraki | Epochal Tsukuba | [Poster Presentation]
On a family of $q$-normal distributions in the framework of $tau$-information geometry Masaru Tanaka (Fukuoka Univ.) IBISML2015-62 |
$tau$-information geometry, that is a new formulation of information geometry, is given by extending a translation opera... [more] | IBISML2015-62 pp.69-73 |
| PRMU, IBISML, IPSJ-CVIM [detail] | 2015-09-14 13:30 |
Ehime | Curved exponential family fitting in the space of normal distribution Jun Fujiki, Masaru Tanaka (Fukuoka Univ.), Shotaro Akaho (AIST) PRMU2015-70 IBISML2015-30 |
We consider the manifold fitting to a given set of points in the space of probability distributions. Although only t... [more] |
PRMU2015-70 IBISML2015-30 pp.19-24 |
|
| NC, IPSJ-BIO, IBISML, IPSJ-MPS (Joint) [detail] |
2015-06-25 10:20 |
Okinawa | Okinawa Institute of Science and Technology | e-Bagging: The Information Geometric Dual of Breiman's Bagging
-- An Application to the Nadaraya-Watson Regression with the k-Nearest Neighbor Crossover Kernel -- Naoki Hamada, Hiroyuki Higuchi, Katsumi Homma (Fujitsu Labs.) IBISML2015-23 |
The $k$-nearest neighbor crossover kernel, which we proposed recently, is a very flexible kernel that is virtually equiv... [more] | IBISML2015-23 pp.187-194 |
| QIT (2nd) |
2015-05-25 13:20 |
Osaka | Osaka University | [Poster Presentation]
Generalization of quantum f-divergence and its geometrical properties Yu Takaoka, Yu Watanabe (YITP, Kyoto Univ.) |
We define a class of generalized quantum f-divergences. They satisfy the non-negativity, CPTP monotonicity, and coincid... [more] |
|
| IBISML | 2013-11-12 15:45 |
Tokyo | Tokyo Institute of Technology, Kuramae-Kaikan | [Poster Presentation]
Performance Comparisons between Dependency Networks and Bayesian Networks Kazuya Takabatake, Shotaro Akaho (AIST) IBISML2013-41 |
Dependency networks are graphical models in which tasks of learning are done by totally local and simple algorithms of i... [more] | IBISML2013-41 pp.39-44 |
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