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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| PN | 2016-11-17 15:05 |
Saitama | KDDI Research, Inc. | A Bayesian-based Virtual Network Reconfiguration in Elastic Optical Path Networks Toshihiko Ohba, Shin'ichi Arakawa, Masayuki Murata (Osaka Univ.)  PN2016-33 |
A typical approach for constructing/reconfiguring a virtual network (VN) is to design an optimal topology and the amount... [more] | PN2016-33 pp.45-50 |
| IBISML | 2016-11-16 15:00 |
Kyoto | Kyoto Univ. | Inference of Classical Spin Model by Multidimensional Multiple Histogram Method Hikaru Takenaka (UTokyo), Kenji Nagata (UTokyo/AIST/JST), Takashi Mizokawa (Waseda Univ.), Masato Okada (UTokyo/RIKEN) IBISML2016-61 |
We propose a novel method for effective Bayesian inference of classical spin model by the multidimensional multiple hist... [more] | IBISML2016-61 pp.109-116 |
| IBISML | 2016-11-17 14:00 |
Kyoto | Kyoto Univ. | Gaussian Markov random field model without periodic boundary conditions Shun Katakami, Hirotaka Sakamoto, Shin Murata, Masato Okada (UTokyo) IBISML2016-83 |
In this study, we discuss Gaussian Markov random field model without periodic boundary conditions. First, we formulate a... [more] | IBISML2016-83 pp.267-274 |
| SS | 2016-03-11 10:50 |
Okinawa | A Prioritization of Combinatorial Testing Using Bayesian Inference Shunya Kawabata (Kyoto Inst. Tech.), Eun-Hye Choi (AIST), Osamu Mizuno (Kyoto Inst. Tech.) SS2015-95 |
An ideal testing detects a large number of faults with a small number of test cases. Combinatorial testing, which focus... [more] |
SS2015-95 pp.115-120 |
|
| NS, IN (Joint) |
2016-03-04 13:50 |
Miyazaki | Phoenix Seagaia Resort | A meal menu recommendation system based on the Bayesian network inference modeling intuitive elements Masahide MIyoshi, Kazumasa Takami (Soka Univ.) IN2015-145 |
We are intuitive to determine the diet menu that we want to eat in a restaurant, in consideration of their own situation... [more] | IN2015-145 pp.217-222 |
| IBISML | 2015-11-27 14:00 |
Ibaraki | Epochal Tsukuba | [Poster Presentation]
Minimum required data amount in Bayesian inference from the viewpoint of specific heat Satoru Tokuda, Kenji Nagata, Masato Okada (Univ. of Tokyo) IBISML2015-74 |
The accuracy of Bayesian inference depends on the number of samples or noise. Sample size or noise level often changes t... [more] | IBISML2015-74 pp.159-166 |
| CCS | 2015-11-10 15:00 |
Kyoto | Inamori Foundation Memorial Building, Kyoto Univ. | Segmental Bayesian estimation of neuronal parameters from spike trains Isao Tokuda, Huu Hoang (Ritsumeikan Univ.) CCS2015-63 |
Multi-electrode recording is now a common technique to simultaneously collect neuronal spike data of a population of the... [more] | CCS2015-63 pp.99-102 |
| NC, MBE | 2015-03-17 13:00 |
Tokyo | Tamagawa University | Latent dynamics estimation from time-series spectral data Shin Murata, Kenji Nagata (Univ. of Tokyo), Makoto Uemura (Hiroshima Univ.), Masato Okada (Univ. of Tokyo/RIKEN) MBE2014-173 NC2014-124 |
Estimation of latent dynamics from time-series data is important problem in a broad range of fields. In this research, w... [more] | MBE2014-173 NC2014-124 pp.319-324 |
| TL | 2014-08-13 10:00 |
Tokyo | The University of Tokyo (Komaba) 18 Bldg. Hall | [Tutorial Lecture]
Fitting linear mixed models using JAGS and Stan: A tutorial Shravan Vasishth, Tanner Sorensen (Univ. of Potsdam) TL2014-28 |
Psycholinguists routinely use linear mixed models (LMMs) for statistical inference. The most widely used tool for this p... [more] | TL2014-28 pp.95-96 |
| SP, IPSJ-SLP (Joint) |
2014-07-25 14:20 |
Iwate | Hotel Hanamaki | [Invited Talk]
Karnel method for Bayesian inference and its applications Kenji Fukumizu (ISM) SP2014-69 |
As a kernel framework for statsitical inference, "kernel mean embedding" has been recently developed, in which probabili... [more] | SP2014-69 pp.37-40 |
| SP, IPSJ-MUS | 2014-05-24 11:30 |
Tokyo | Underdetermined Blind Separation of Moving Sources Based on Probabilistic Modeling Takuya Higuchi, Norihiro Takamune, Tomohiko Nakamura (Univ. of Tokyo), Hirokazu Kameoka (Univ. of Tokyo/NTT) SP2014-20 |
This paper deals with the problem of the underdetermined blind separation and tracking of moving sources. In practical s... [more] | SP2014-20 pp.211-216 |
|
| NC, MBE (Joint) |
2014-03-18 14:20 |
Tokyo | Tamagawa University | 3D Superresolution of Microscopic Images based on Variational Bayesian Inference via Chebyshev polynomials approximation Yasuhiro Imoto, Shin-ichi Maeda, Shin Ishii (Kyoto Univ.) NC2013-111 |
Optical microscopes are used to elucidate changes in cellular functions mediated by morphological changes of cells in vi... [more] | NC2013-111 pp.133-138 |
| NC, NLP | 2013-01-24 11:10 |
Hokkaido | Hokkaido University Centennial Memory Hall | depth estimation from microscopic images using Bayesian inference Yasuhiro Imoto, Shin-ichi Maeda, Shin Ishii (Kyoto Univ.) NLP2012-109 NC2012-99 |
In cellular biology, it is important to know 3D cellular shape to understand the cellular function. However, existing mi... [more] | NLP2012-109 NC2012-99 pp.31-36 |
| CS | 2012-11-22 10:30 |
Hokkaido | Kitayuzawa Meisuitei, Hokkaido | An Experimental examination of Bayesian estimation method destination by using ZigBee Takuya Sugishita, Hiroshi Takase, Takefumi Hiraguri (NIT) CS2012-75 |
In the present study, it proposes the technique for presuming the destination and the migration pathway of the movement ... [more] | CS2012-75 pp.65-69 |
| IBISML | 2012-11-07 15:30 |
Tokyo | Bunkyo School Building, Tokyo Campus, Tsukuba Univ. | Bayesian image super-resolution of large image with a compound MRF and estimating registration parameters Toshiki Kinoshita, Seiji Miyoshi (Kansai Univ.) IBISML2012-35 |
Super-resolution is a technique to estimate a higher resolution image from low-resolution images. In this manuscript, we... [more] | IBISML2012-35 pp.9-16 |
| IBISML | 2012-11-07 15:30 |
Tokyo | Bunkyo School Building, Tokyo Campus, Tsukuba Univ. | Nested-Hierarchical Dirichlet Process Mixtures for Simultaneous Document-Topic Clustering Shoji Tominaga, Masamichi Shimosaka, Rui Fukui, Tomomasa Sato (Univ. of Tokyo) IBISML2012-56 |
In this paper, we propose a nonparametric Bayesian framework for natural language processing (NLP). Our framework is bas... [more] | IBISML2012-56 pp.157-164 |
| MI | 2012-07-19 15:40 |
Yamagata | Yamagata Univ. | Bayesian Inference Approach to Visualize Neuroreceptor Density using Positron Emission Tomography without Arterial Blood Sampling Takahiro Kozawa, Hidekata Hontani (NIT), Kazuya Sakaguchi (Kitasato Univ), Muneyuki Sakata (TMGHIG), Yuichi Kimura (NIRS) MI2012-26 |
A Bayesian approach to de-noise tissue time activity curves (tTAC) is proposed in order to quantitatively visualize neur... [more] | MI2012-26 pp.29-34 |
| IA, SITE, IPSJ-IOT [detail] | 2012-03-16 10:00 |
Hokkaido | Hokkaido Univ. | Development on topic providing system with inference of daily life behavior Seiji Suzuki, Nobuhiko Matsuura (Shizuoka Univ.), Ken Ohta, Hiroshi Inamura (NTT DOCOMO), Tadanori Mizuno (AIT), Hiroshi Mineno (Shizuoka Univ.) SITE2011-43 IA2011-93 |
Recently, it is said that face-to-face communication skills are slipping.In this paper, we propose the topic providing s... [more] | SITE2011-43 IA2011-93 pp.149-154 |
| MBE, NC (Joint) |
2012-03-14 16:50 |
Tokyo | Tamagawa University | Bayesian Network Associative Memories Hiroaki Hasegawa, Masafumi Hagiwara (Keio Univ.) NC2011-146 |
In this paper, we propose Bayesian Network Associative Memories (BNAMs) for modeling associative memories with Bayesian ... [more] | NC2011-146 pp.147-152 |
| IBISML | 2012-03-12 15:30 |
Tokyo | The Institute of Statistical Mathematics | Apprenticeship Learning for Model Parameters of Partially Observable Environments Takaki Makino (Univ. of Tokyo), Johane Takeuchi (HRI-JP) IBISML2011-94 |
We consider apprentice learning, i.e., to make an agent learn a task by observing an expert demonstrating the task, in a... [more] | IBISML2011-94 pp.49-54 |
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