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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 15 of 15  /   
Committee Date Time Place Paper Title / Authors Abstract Paper #
MI 2024-03-03
09:41
Okinawa OKINAWAKEN SEINENKAIKAN
(Primary: On-site, Secondary: Online)
A preliminary study on deep causal discovery model for image classification
Ryohei Motoda, Megumi Nakao (Kyoto Univ.) MI2023-33
Although saliency map used in image classification can visualize the regions correlated with predicted class, it cannot ... [more] MI2023-33
pp.11-14
SIP, SP, EA, IPSJ-SLP [detail] 2024-02-29
15:10
Okinawa
(Primary: On-site, Secondary: Online)
Lightweight and Interpretable Deep Learning Model for EEG-Based Sleep Stage Classification
Aozora Ito, Toshihisa Tanaka (TUAT) EA2023-82 SIP2023-129 SP2023-64
Sleep scoring by experts is necessary for diagnosing sleep disorders. EEG is one of the essential physiological data for... [more] EA2023-82 SIP2023-129 SP2023-64
pp.127-132
IBISML 2022-09-15
14:00
Kanagawa Keio Univ. (Yagami Campus)
(Primary: On-site, Secondary: Online)
Interpretable Model Combining statements and DNN
Ryo Okuda, Yuya Yoshikawa (STAIR) IBISML2022-36
In this study, we propose a method that achieves both interpretability of Decision Tree and the prediction accuracy of D... [more] IBISML2022-36
pp.25-30
NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] 2022-06-27
17:25
Okinawa
(Primary: On-site, Secondary: Online)
Additive Cumulative Link Model with Total Variation Regularization
Hiroya Iyori, Shin Matsushima (Univ. of Tokyo) NC2022-8 IBISML2022-8
In many fields such as medical research and social science, data on an ordinal scale are often obtained.
Problems in wh... [more]
NC2022-8 IBISML2022-8
pp.69-75
SIP, BioX, IE, MI, ITE-IST, ITE-ME [detail] 2022-05-20
16:20
Kumamoto Kumamoto University Kurokami Campus
(Primary: On-site, Secondary: Online)
Visualization of Important Features for Classifier Decisions using Deep Image Synthesis
Yushi Haku, Megumi Nakao, Tetsuya Matsuda (Kyoto Univ.) SIP2022-28 BioX2022-28 IE2022-28 MI2022-28
It is difficult to know the basis for the decisions of machine learning models, and it is necessary to provide a highly ... [more] SIP2022-28 BioX2022-28 IE2022-28 MI2022-28
pp.144-149
IBISML 2022-01-18
13:00
Online Online Local Explanation of Graph Neural Network through Predictive Graph Mining
Hinata Asahi, Masayuki Karasuyama (NIT) IBISML2021-23
Graph Neural Networks (GNNs) have attracted wide attention in the data science community. However, predictions of GNNs a... [more] IBISML2021-23
pp.37-44
MI 2021-03-15
13:45
Online Online Surgical planning model generation by extracting important feature sets in mandibular reconstruction
Kazuki Nagai, Megumi Nakao (Kyoto Univ.), Nobuhiro Ueda (Nara Medical Univ.), Yuichiro Imai (Rakuwakai Otowa Hospital), Toshihide Hatanaka, Tadaaki Kirita (Nara Medical Univ.), Tetsuya Matsuda (Kyoto Univ.) MI2020-54
Because implicit medical knowledge and experience are used to perform medical treatment, such decisions must be clarifie... [more] MI2020-54
pp.29-34
MI 2021-03-15
14:00
Online Online Analysis of important features in surgical planning for mandibular reconstruction among multiple surgeons
Yusuke Hatakeyama, Kazuki Nagai, Megumi Nakao, Tetsuya Matsuda (Kyoto Univ.) MI2020-55
Surgeons perform surgical treatment by considering the facilities and policies of medical institutions and their own exp... [more] MI2020-55
pp.35-40
SIS 2020-12-01
14:25
Online Online Interpretability of deep neural networks with self-organizing map modules.
Takahiro Sono, Keiichi Horio (KIT) SIS2020-32
In recent years, the technology of neural networks has made great progress due to the improvement of computational power... [more] SIS2020-32
pp.27-30
RISING
(2nd)
2019-11-27
13:55
Tokyo Fukutake Learning Theater, Hongo Campus, Univ. Tokyo [Poster Presentation] A Study on Interpretation of Review Classification by SVM and DNN
Kosuke Nakamura, Saneyasu Yamaguchi (Kogakuin Univ.)
Deep learning has achieved significant improvement in various tasks such as natural language processing. However, it is ... [more]
VLD, DC, CPSY, RECONF, ICD, IE, IPSJ-SLDM, IPSJ-EMB, IPSJ-ARC
(Joint) [detail]
2019-11-14
16:35
Ehime Ehime Prefecture Gender Equality Center Domain Knowledge-aware Machine Learning System with Rule-based Guiding
Tomoaki Shikina, Daichi Teruya, Hironori Nakajo (TAT) CPSY2019-44
Data-driven methods in machine learning rely only on the statistical nature of the data. Therefore, its predictions coul... [more] CPSY2019-44
pp.23-28
PRMU, BioX 2019-03-17
14:45
Tokyo   A Study of Business Interpretation Technique for AI Predictions
Naoaki Yokoi, Masashi Egi (Hitachi, Ltd.) BioX2018-39 PRMU2018-143
(To be available after the conference date) [more] BioX2018-39 PRMU2018-143
pp.61-66
AI 2018-12-07
14:40
Fukuoka   AI2018-28 Many researches targeting review of goods and services are doing today. Although research is conducted from various view... [more] AI2018-28
pp.15-18
IBISML 2018-11-05
15:10
Hokkaido Hokkaido Citizens Activites Center (Kaderu 2.7) [Poster Presentation] Compensated Integrated Gradients for Visualization of Features Contributing to EEG Classification
Kazuki Tachikawa, Yuji Kawai, Jihoon Park, Minoru Asada (Osaka Univ.) IBISML2018-76
Integrated gradients method has been widely employed to evaluate the degrees of contribution of input features to classi... [more] IBISML2018-76
pp.241-247
SIP, CAS, MSS, VLD 2017-06-19
13:00
Niigata Niigata University, Ikarashi Campus [Invited Talk] Composite Variables and Ensemble: Introduction to Forest Regression and Additive Models
Ichigaku Takigawa (Hokkaido Univ.) CAS2017-8 VLD2017-11 SIP2017-32 MSS2017-8
Machine learning, supervised machine learning in particular, now becomes one of daily tools in signal processing such as... [more] CAS2017-8 VLD2017-11 SIP2017-32 MSS2017-8
p.43
 Results 1 - 15 of 15  /   
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