Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
RCC, ISEC, IT, WBS |
2024-03-13 - 2024-03-14 |
Osaka |
Osaka Univ. (Suita Campus) |
Comparison of Scale Parameter Dependence of Estimation Performance in Sparse Bayesian Linear Regression Model with Variance Gamma Prior Distribution and t-Prior Distribution Kazuaki Murayama (UEC) IT2023-135 ISEC2023-134 WBS2023-123 RCC2023-117 |
In the sparse estimation with linear regression model, the variance gamma distribution and t-distribution can be used as... [more] |
IT2023-135 ISEC2023-134 WBS2023-123 RCC2023-117 pp.374-379 |
NS, IN (Joint) |
2024-02-29 10:10 |
Okinawa |
Okinawa Convention Center |
Multimodal Object Recognition Method Using Bayesian Attractor Model For 3D Point Clouds and RGB Images Haruhito Ando, Daichi Kominami, Ryoga Seki, Masayuki Murata, Hideyuki Shimonishi (Osaka Univ.) NS2023-192 |
Beyond 5G/6G, technology is driving the development of digital twins. In recent years, the amount of information that ca... [more] |
NS2023-192 pp.119-124 |
IBISML |
2023-12-21 10:55 |
Tokyo |
National Institute of Informatics (Primary: On-site, Secondary: Online) |
On the benefits of Partial Stochastic Bayesian Neural Networks Koki Sato, Daniel Andrade (Hiroshima Univ.) IBISML2023-36 |
Bayesian neural networks (BNNs) can model uncertainty in the prediction results better than ordinary neural networks. Ho... [more] |
IBISML2023-36 pp.37-41 |
VLD, DC, RECONF, ICD, IPSJ-SLDM [detail] |
2023-11-17 14:50 |
Kumamoto |
Civic Auditorium Sears Home Yume Hall (Primary: On-site, Secondary: Online) |
Hardware Compression Method Applying Bernoulli Approximation for Bayesian Neural Networks Taisei Saito, Kota Ando, Tetsuya Asai (Hokkaido Univ.) VLD2023-73 ICD2023-81 DC2023-80 RECONF2023-76 |
This study focuses on efficiently lightweighting Bayesian deep learning algorithms and implementing them on FPGA. It com... [more] |
VLD2023-73 ICD2023-81 DC2023-80 RECONF2023-76 pp.221-226 |
NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] |
2023-06-30 13:55 |
Okinawa |
OIST Conference Center (Primary: On-site, Secondary: Online) |
Exploring Regioselective Catalysts with Hierarchical Bandits Hongyuan Guo, Koji Tabata, Yoshihiro Matsumura, Tamiki Komatsuzaki (Hokkaido Univ.) NC2023-17 IBISML2023-17 |
In selective chemical reactions, controlling the reaction site is crucial in synthetic organic chemistry. This study foc... [more] |
NC2023-17 IBISML2023-17 pp.106-112 |
RCC, ISEC, IT, WBS |
2023-03-14 15:20 |
Yamaguchi |
(Primary: On-site, Secondary: Online) |
Estimation Performance of Sparse Bayesian Linear Regression model with t-distribution Kazuaki Murayama (UEC) IT2022-105 ISEC2022-84 WBS2022-102 RCC2022-102 |
In the sparse estimation with linear regression model, the t-distribution can be used as a prior distribution. We analyz... [more] |
IT2022-105 ISEC2022-84 WBS2022-102 RCC2022-102 pp.236-241 |
NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] |
2022-06-27 14:25 |
Okinawa |
(Primary: On-site, Secondary: Online) |
A Bagging Method to Improve the Accuracy of Gaussian Process Regression for Neural Architecture Search Rion Hada, Masao Okita, Fumihiko Ino (Osaka Univ.) NC2022-2 IBISML2022-2 |
The goal of this study is to improve performance estimation for neural network architectures in neural architecture sear... [more] |
NC2022-2 IBISML2022-2 pp.6-13 |
CCS, NLP |
2022-06-10 16:45 |
Osaka |
(Primary: On-site, Secondary: Online) |
Motion artifact reduction in EEG recordings using the multivariate temporal response function of acceleration signals with hyperparameter estimation Hiroaki Umehara, Yusuke Yokota (NICT), Masato Okada (UTokyo/NICT), Yasuishi Naruse (NICT) NLP2022-24 CCS2022-24 |
The recent advances of wearable electroencephalography (EEG) systems with dry electrodes provide the realization of brai... [more] |
NLP2022-24 CCS2022-24 pp.123-128 |
NS, IN (Joint) |
2022-03-11 11:40 |
Online |
Online |
A Study on Bayesian Spatial and Temporal Modeling Approach to Environmental Feature Inference Using Driving Signals From Vehicles Yukio Ogawa (Muroran-IT), Go Hasegawa (Tohoku Univ.), Masayuki Murata (Osaka Univ.) IN2021-43 |
Connected vehicles become an ambient sensing platform, as a number of different signals that they record become availabl... [more] |
IN2021-43 pp.73-78 |
CQ, IMQ, MVE, IE (Joint) [detail] |
2022-03-10 18:30 |
Online |
Online (Zoom) |
Implementation and evaluation of an object recognition method for Digital Twin using cognitive mechanism of the Brain Kaito Kubo, Ryoga Seki, Daichi Kominiami, Hideyuki Shimonishi, Masayuki Murata (Osaka Univ.), Masaya Fujiwaka (NEC) CQ2021-125 |
It is desired to construct a digital twin that can sense objects such as people and objects in the real world and repres... [more] |
CQ2021-125 pp.136-141 |
IBISML |
2022-03-09 09:40 |
Online |
Online |
[Invited Talk]
--- Satoru Tokuda (Kyushu Univ.) IBISML2021-40 |
Plasma is the fourth state of matter, in which individual electrons and ions move around at various speeds. The velocity... [more] |
IBISML2021-40 p.33 |
R |
2021-10-22 14:25 |
Online |
Online |
[Invited Talk]
Field Lifetime Data Analysis with Left-truncation and Right-censoring
-- Statistical Inference and Reliability Prediction based on Parametric Models -- Takeshi Emura (Kurume Univ.), Hirofumi Michimae (Kitasato Univ.) R2021-31 |
In applications of reliability analyses, a dataset may be collected during a period of time to observe failure events. L... [more] |
R2021-31 pp.7-12 |
IT |
2021-07-09 13:25 |
Online |
Online |
A Note on the Reduction of Computational Complexity for Linear Regression Model Including Cluster Explanatory Variables and Regression Explanatory Variables
-- Bayes Optimal Prediction and Sub-Optimal Algorithm -- Sho Kayama (Waseda Univ.), Shota Saito (Gunma Univ.), Toshiyasu Matsushima (Waseda Univ.) IT2021-24 |
By considering the probability model with the structure that the data is divided into clusters and each cluster has an i... [more] |
IT2021-24 pp.51-56 |
CS, CQ (Joint) |
2021-05-14 11:15 |
Online |
On-line |
Proposal and Evaluation of an Object Estimation Method Inspired by Multimodal Information Processing in the Brain Ryoga Seki, Daichi Kominami, Hideyuki Shimonishi, Masayuki Murata (Osaka Univ.), Masaya Fujiwaka, Kosuke Nogami (NEC) CQ2021-14 |
In order to realize the digital twin, it is desired to instantly identify various objects in the real world through sens... [more] |
CQ2021-14 pp.59-64 |
WBS, IT, ISEC |
2021-03-05 10:15 |
Online |
Online |
A Proposal for Causal Inference with Subjective Evaluation Daichi Ikeda, Hikaru Morita (Graduate School of Kanagawa Univ.) IT2020-146 ISEC2020-76 WBS2020-65 |
Machine learning techniques such as deep learning are often used for identification and personal matching in information... [more] |
IT2020-146 ISEC2020-76 WBS2020-65 pp.208-212 |
MBE, NC (Joint) |
2020-12-18 17:30 |
Online |
Online |
Parameter inference using Approximate Bayesian Computations for the intermittent control model on postural sway data: A comparison between healthy people and patients with Parkinson's disease Yasuyuki Suzuki, Akihiro Nakamura (Osaka Univ.), Takuyuki Endo, Saburo Sakoda (Osaka Toneyama Medical Center), Taishin Nomura (Osaka Univ.) MBE2020-25 |
Feedback control by the central nervous system is indispensable for stabilizing upright posture during quiet standing. W... [more] |
MBE2020-25 pp.25-30 |
MI, IE, SIP, BioX, ITE-IST, ITE-ME [detail] |
2020-05-28 12:40 |
Online |
Online |
[Special Talk]
Generalization of coherent point drift and its acceleration Osamu Hirose (Kanazawa Univ.) SIP2020-1 BioX2020-1 IE2020-1 MI2020-1 |
Point set registration is to find point-to-point correspondences between point sets, each of which represents the shape ... [more] |
SIP2020-1 BioX2020-1 IE2020-1 MI2020-1 pp.1-3 |
NC, MBE (Joint) |
2020-03-05 13:00 |
Tokyo |
University of Electro Communications (Cancelled but technical report was issued) |
Bayesian learning curve for the case when the optimal distribution is not unique Shuya Nagayasu, Sumio Watanabe (Tokyo Tech) NC2019-94 |
Bayesian inference is a widely used statistical method. Asymptotic behaviors of generalization loss and free energy in B... [more] |
NC2019-94 pp.107-112 |
NC, MBE (Joint) |
2020-03-05 16:10 |
Tokyo |
University of Electro Communications (Cancelled but technical report was issued) |
Improvement of neuronal ensemble inference by Monte Carlo method and applying to real data Shun Kimura, Koujin Takeda (Ibaraki Univ.), Keisuke Ota (Riken) NC2019-101 |
In this work, we propose an improved inference algorithm for neuronal ensembles, which can classify neurons into ensembl... [more] |
NC2019-101 pp.149-154 |
CQ, CBE (Joint) |
2020-01-17 09:40 |
Tokyo |
NHK Science & Technology Research Laboratories |
Bayesian channel selection method for LoRaWAN under unpredictable wireless channel fluctuations Daichi Kominami (Osaka Univ.), Yohei Hasegawa, Kosuke Nogami, Hideyuki Shimonishi (NEC), Masayuki Murata (Osaka Univ.) CQ2019-122 |
Internet of Things (IoT) become a common term used in society. LPWA technology is attracting attention as one of its ele... [more] |
CQ2019-122 pp.83-88 |