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All Technical Committee Conferences (Searched in: Recent 10 Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| NC, MBE (Joint) |
2025-03-06 16:20 |
Tokyo | (Primary: On-site, Secondary: Online) |
Global Convergence Analysis of Distributed Lasso Algorithm based on Alternating Direction Method of Multipliers Naoki Toda, Tsuyoshi Migita, Norikazu Takahashi (Okayama Univ.)  NC2024-77 |
The alternating direction method of multipliers (ADMM) is one of the representative computational methods for lasso (lea... [more] | NC2024-77 pp.85-90 |
| ITS, IE, ITE-MMS, ITE-ME, ITE-AIT [detail] | 2024-02-20 12:45 |
Hokkaido | Hokkaido Univ. | 3D CG Coded Image Noise Removal and Quality Assessment Based on Optimal Design of Total Variation Regularization Norifumi Kawabata (Kanazawa Gakuin Univ.) ITS2023-67 IE2023-56 |
Sparse coding techniques, which reproduce and represent images with as few combinations as possible from a small amount ... [more] | ITS2023-67 IE2023-56 pp.112-117 |
| SIP, IT, RCS | 2024-01-18 11:45 |
Miyagi | (Primary: On-site, Secondary: Online) |
A Study on Massive MIMO Channel Estimation Based on Sparse Bayesian Learning Using Hierarchical Model Kengo Furuta, Takumi Takahashi, Kenta Ito (Osaka Univ.), Shinsuke Ibi (Doshisha Uni.) IT2023-34 SIP2023-67 RCS2023-209 |
Massive multi-input multi-output (MIMO) channels are known to have pseudo-sparsity in the angular (beam) domain, and it ... [more] | IT2023-34 SIP2023-67 RCS2023-209 pp.25-30 |
| NLP, CAS | 2023-10-07 13:20 |
Gifu | Work plaza Gifu | Proposal and evaluation of a distributed lasso algorithm based on alternating direction multiplier method Naoki Toda, Tsuyoshi Migita, Norikazu Takahashi (Okayama Univ.) CAS2023-55 NLP2023-54 |
Lasso is widely known as a sparse estimation method for regression coefficients in linear regression models, and the Alt... [more] | CAS2023-55 NLP2023-54 pp.111-116 |
| NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] | 2023-06-29 13:30 |
Okinawa | OIST Conference Center (Primary: On-site, Secondary: Online) |
Selective Inference for a Combination of Feature Selection Algorithms Tatsuya Matsukawa (Nagoya Univ.), Daiki Miwa (NITech), Vo Nguyen Le Duy (RIKEN), Koichi Taji (Nagoya Univ.), Ichiro Takeuchi (Nagoya Univ./RIKEN) NC2023-1 IBISML2023-1 |
In data-driven science, classical statistical hypothesis testing does not provide an adequate reliability assessment bec... [more] | NC2023-1 IBISML2023-1 pp.1-8 |
| ICTSSL | 2022-07-29 13:55 |
Osaka | Kansai University (Primary: On-site, Secondary: Online) |
Behavior Analysis of Evacuees using Sparse Structure Learning for Development of Emergency Rescue Evacuation Support System Yeboon Yun, Tomotaka Wada (Kansai Univ.) ICTSSL2022-13 |
We have developed the Emergency Rescue Evacuation Support System (ERESS) which is designed to automatically detect disas... [more] | ICTSSL2022-13 pp.16-21 |
| 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 |
| NC, MBE (Joint) |
2021-03-03 13:00 |
Online | Online | Hybrid Sparsity in Convolutional Neural Networks Shoma Noguchi, Yukari Yamauchi (Nihon Univ.) NC2020-46 |
Convolutional neural networks (CNNs) have achieved high accuracy in areas such as image classification and object detect... [more] | NC2020-46 pp.21-24 |
| US | 2021-02-22 16:25 |
Online | Online | Inverse wave analysis for crack opening displacement using sparse modeling Sohichi Hirose, Ayumi Wakita (Tokyo Tech) US2020-73 |
Sparse modeling has been applied to many inverse problems as an approximate method to solve an equation with sparsely ... [more] |
US2020-73 pp.35-38 |
| MVE | 2020-09-09 14:00 |
Online | Online | Shitsukan Representation Based on Kansei Model Using Neural Style Feature Natsuki Sunda, Iori Tani (Kwansei Gakuin Univ.), Kensuke Tobitani (The Univ. of Nagasaki), Atsushi Takemoto, Yusuke Tani, Noriko Nagata (Kwansei Gakuin Univ.), Nobufumi Morita (Couture Digital) MVE2020-18 |
In this research, we focus on affective texture, which comprises the visual impressions evoked by surface properties, su... [more] | MVE2020-18 pp.38-43 |
| NC, MBE (Joint) |
2020-03-05 16:35 |
Tokyo | University of Electro Communications (Cancelled but technical report was issued) |
Sparse STC estimation of suppressive elements for neurons in primary visual cortex Reiji Tanaka (Osaka Univ.), Kota Sasaki (Osaka Univ./NICT), Hirotaka Sakamoto, Yoshihiro Nagano (Tokyo Univ.), Yonghao Yue (Aoyama Gakuin Univ.), Masato Okada (Tokyo Univ./RIKEN), Izumi Ohzawa (Osaka Univ./NICT) NC2019-102 |
To improve a functional model for visual neurons, we have been developing a novel technique (sparse STC) where a spike-t... [more] | NC2019-102 pp.155-159 |
| MI | 2020-01-29 10:45 |
Okinawa | OKINAWAKEN SEINENKAIKAN | Proposal of Extraction Method of Important Features in Surgical Planning for Mandibular Reconstruction Kazuki Nagai, Megumi Nakao (Kyoto Univ.), Nobuhiro Ueda (Nara Medical Univ.), Yuichiro Imai (Rakuwakai Otowa Hospital), Tadaaki Kirita (Nara Medical Univ.), Tetsuya Matsuda (Kyoto Univ.) MI2019-70 |
As implicit medical knowledge and experience are used to perform medical treatment, clarification of decision making is ... [more] | MI2019-70 pp.23-28 |
| MBE, NC | 2019-10-11 15:00 |
Miyagi | Analysis of diffuse lung disease shadows using Bolasso feature selection method Akihiro Endo (UEC), Kenji Nagata (NIMS), Shoji Kido (Osaka Univ.), Hayaru Shouno (UEC) MBE2019-33 NC2019-24 |
Diffuse lung disease is an intractable disease and abnormal shadows appear on lung X-ray CT images. Since various patte... [more] |
MBE2019-33 NC2019-24 pp.23-27 |
|
| NC, IBISML, IPSJ-MPS, IPSJ-BIO [detail] | 2019-06-17 15:00 |
Okinawa | Okinawa Institute of Science and Technology | A model selection criterion for LASSO estimate with scaling Katsuyuki Hagiwara (Mie Univ.) IBISML2019-5 |
To relax a bias problem in LASSO (Least Absolute Shrinkage and election Operator), there have been several studies inclu... [more] | IBISML2019-5 pp.27-34 |
| MICT, MI | 2018-11-06 09:40 |
Hyogo | University of Hyogo | Displacement estimation of pancreatic cancer based on multidimensional features of multiple surrounding organs for real-time radiation therapy Taiji Iwai, Megumi Nakao, Mitsuhiro Nakamura, Tetsuya Matsuda (Kyoto Univ.) MICT2018-39 MI2018-39 |
This paper proposes a method to estimate displacements of pancreatic cancer based on multidimensional features of multip... [more] | MICT2018-39 MI2018-39 pp.7-12 |
| IBISML | 2018-11-05 15:10 |
Hokkaido | Hokkaido Citizens Activites Center (Kaderu 2.7) | [Poster Presentation]
Estimation of Sparse Basis Representation for Non-periodic data Shun Katakami, Hirotaka Sakamoto, Yasuhiko Igarashi, Masato Okada (Univ. Tokyo) IBISML2018-71 |
In this research, we propose a method to estimate a sparse basis representation for non-periodic data. For periodic data... [more] | IBISML2018-71 pp.205-212 |
| IBISML | 2018-11-05 15:10 |
Hokkaido | Hokkaido Citizens Activites Center (Kaderu 2.7) | IBISML2018-87 |
A learning algorithm to perform sparse estimation method can estimate effective parameters of a polynomial regression mo... [more] | IBISML2018-87 pp.321-328 |
| IBISML | 2018-11-05 15:10 |
Hokkaido | Hokkaido Citizens Activites Center (Kaderu 2.7) | [Poster Presentation]
Analysis of Empirical Bayes Estimation for Three Parameter Group Lasso Tsukasa Yoshida, Kazuho Watanabe (Toyohashi Tech) IBISML2018-93 |
As sparse estimation methods, Lasso and Group Lasso are often used for wide applications. It is necessary for successful... [more] | IBISML2018-93 pp.367-372 |
| IBISML | 2018-11-05 15:10 |
Hokkaido | Hokkaido Citizens Activites Center (Kaderu 2.7) | [Poster Presentation]
Active Learning in Sparse Linear Regression Models via Selective Inference Yuta Umezu (NIT), Ichiro Takeuchi (NIT/NIMS/RIKEN) IBISML2018-95 |
In order to efficiently estimate interested parameter, one can design sampling strategy by defining some criterion on th... [more] | IBISML2018-95 pp.381-388 |
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