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 |
NC, MBE (Joint) |
2024-03-12 13:30 |
Tokyo |
The Univ. of Tokyo (Primary: On-site, Secondary: Online) |
Diffusion-Based Immediate Adversarial Purification Yuito Narisawa, Motonobu Hattori (Yamanashi Univ.) NC2023-56 |
Neural networks have achieved high performance in image classification, but there is a problem known as Adversarial Exam... [more] |
NC2023-56 pp.75-80 |
MI |
2024-03-03 09:05 |
Okinawa |
OKINAWAKEN SEINENKAIKAN (Primary: On-site, Secondary: Online) |
[Short Paper]
Generation of Counterfactual Pathology Images of Malignant Lymphoma using Diffusion Models Ryoichi Koga, Tatsuya Yokota (NIT), Kouichi Ohshima, Hiroaki Miyoshi, Miharu Nagaishi (Kurume Univ.), Noriaki Hashimoto (RIKEN), Ichiro Takeuchi (Nagoya Univ.), Hidekata Hontani (NIT) MI2023-30 |
Malignant lymphoma has more than 70 subtypes. In the pathological diagnosis, a pathological image is observed to identif... [more] |
MI2023-30 pp.1-2 |
SIP, SP, EA, IPSJ-SLP [detail] |
2024-03-01 10:40 |
Okinawa |
(Primary: On-site, Secondary: Online) |
Substitution of Implicit Linguistic Information in Beam Search Decoding Using CTC-based Speech Recognition Models Tatsunari Takagi, Yukoh Wakabayashi (TUT), Atsunori Ogawa (NTT), Norihide Kitaoka (TUT) EA2023-106 SIP2023-153 SP2023-88 |
The rise of neural networks in the field of automatic speech recognition has notably improved the accuracy of speech rec... [more] |
EA2023-106 SIP2023-153 SP2023-88 pp.268-273 |
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 |
R |
2023-09-28 14:20 |
Fukuoka |
(Primary: On-site, Secondary: Online) |
Copula models based on left-truncated and competing risks data
-- Likelihood inference based on field studies -- Takeshi Emura (ISM), Hirofumi Michimae (Kitasato Univ.) R2023-39 |
In the collection method of failure data (field life data) in field tests, unobserved failure occurs before the collecti... [more] |
R2023-39 pp.12-15 |
R |
2023-09-28 15:20 |
Fukuoka |
(Primary: On-site, Secondary: Online) |
Polynomial Failure Models: Theory and Applications Tadashi Dohi, Hiroyuki Okamura (Hiroshima Univ.) R2023-41 |
In this paper we summarize two polynomial failure models, where the lifetime distributions are described by canonical po... [more] |
R2023-41 pp.22-27 |
IA, ICSS |
2023-06-21 09:55 |
Saga |
Saga Univ. (Primary: On-site, Secondary: Online) |
A Proposal for Access Control Method based on File Relation Inference from Users Behavior Yuki Kodaka (SOKENDAI), Hirokazu Hasegawa, Hiroki Takakura (NII) IA2023-8 ICSS2023-8 |
File access control is an effective method for protecting information from unauthorized access both within and outside a... [more] |
IA2023-8 ICSS2023-8 pp.40-47 |
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 |
TL |
2023-03-11 14:15 |
Online |
Online |
Emergent Inference in Grammatical Machineries
-- Acquisition of Associative Knowledge into Deductive Systems -- Yasunari Harada (Waseda Univ.) TL2022-39 |
The essence of linguistic communication lies in "exchange of meanings" and "meaningful exchanges of messages." In recent... [more] |
TL2022-39 pp.30-35 |
HWS, VLD |
2023-03-01 11:50 |
Okinawa |
(Primary: On-site, Secondary: Online) |
Acceleration of Memristor Modeling Based on Machine Learning Using Gaussian Process Yuta Shintani, Michiko Inoue (Naist), Michihiro Shintani (Kyoto Institute of Technology) VLD2022-75 HWS2022-46 |
There has been a great deal of research into the development of domain-specific circuits for multiply-and-accumulate pro... [more] |
VLD2022-75 HWS2022-46 pp.13-18 |
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 |
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 |
NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] |
2021-06-28 17:15 |
Online |
Online |
Non-approximate Inference for Collective Graphical Models on Path Graphs via Discrete Difference of Convex Algorithm Yasunori Akagi, Naoki Marumo, Hideaki Kim, Takeshi Kurashima, Hiroyuki Toda (NTT) NC2021-10 IBISML2021-10 |
The importance of aggregated count data, which is calculated from the data of multiple individuals, continues to increas... [more] |
NC2021-10 IBISML2021-10 pp.70-77 |
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 |
IBISML |
2021-03-04 14:40 |
Online |
Online |
IBISML2020-59 |
In the machine learning tasks where the training data is scarce, domain adaptation (DA) is a promising methodology that ... [more] |
IBISML2020-59 p.78 |
IBISML |
2020-10-21 09:45 |
Online |
Online |
IBISML2020-18 |
A symbol emergence system is a multi-agent system where each autonomous agent forms internal representations through int... [more] |
IBISML2020-18 pp.34-35 |
PRMU, IPSJ-CVIM |
2020-03-17 16:00 |
Kyoto |
(Cancelled but technical report was issued) |
Acceleration of Deep Learning Inference by Model Cascading Shohei Enomoto, Takeharu Eda (NTT) PRMU2019-98 |
In recent years, various applications have appeared due to the development of deep learning and the spread of IoT device... [more] |
PRMU2019-98 pp.203-208 |
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 |