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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| MSS, SS | 2025-01-13 10:50 |
Kagoshima | (Kagoshima) | Application of the Statistical Test Rule Induction Method to Classification Problems and Comparisons with the Neural Network Method Ji Kaikuan, Tomoshi Hatakeyama, Tetsuro Saeki (Yamaguchi Univ.), Yuichi Kato (Shimane Univ.)  MSS2024-57 SS2024-36 |
After pointing out the problems of the conventional Rough Sets’ methods that induce if-then rules hidden in a dataset ca... [more] | MSS2024-57 SS2024-36 pp.76-81 |
| IBISML | 2024-12-21 11:10 |
Hokkaido | Lecture room 1 (D101), Graduate School of Environmental Science (Hokkaido, Online) (Primary: On-site, Secondary: Online) |
Selective Inference for Auto Feature Engineering Tatsuya Matsukawa, Tomohiro Shiraishi (Nagoya Univ.), Shuichi Nishino (Nagoya Univ./RIKEN), Teruyuki Katsuoka (Nagoya Univ.), Ichiro Takeuchi (Nagoya Univ./RIKEN) IBISML2024-46 |
Auto Feature Engineering (AFE) is the process of automatically generating meaningful features from raw data to improve t... [more] | IBISML2024-46 pp.100-107 |
| ET | 2024-12-14 10:00 |
Fukuoka | Kyushu Institute of Technology(Iizuka Campus) (Fukuoka) | A Study on Usage of Statistical Surveys as Teaching Materials for Introduction to Data Wrangling Katsumi Yoshine (Nanzan Univ.) ET2024-48 |
In data analysis classes for undergraduate students, fictitious data that have been formatted are often used as teaching... [more] | ET2024-48 pp.8-11 |
| SITE, LOIS, ISEC | 2024-11-14 14:35 |
Fukuoka | (Fukuoka) | Statistical Model Analysis of Content Services Based on Viewer-Centric Data Utilization Yasuhiro Murasaki (NHK) ISEC2024-70 SITE2024-67 LOIS2024-34 |
While the use of viewing data makes it possible to provide content services tailored to the preferences of individual us... [more] | ISEC2024-70 SITE2024-67 LOIS2024-34 pp.50-57 |
| ET | 2024-07-27 15:05 |
Ehime | Ehime University (Johoku Campus) (Ehime) | Proposition of Metadata for Development of Teaching Materials for Graphing Exercises using Public Documents Katsumi Yoshine (Nanzan Univ.) ET2024-17 |
In First-Year Education, spreadsheet exercises as part of data literacy education for undergraduate students in the soci... [more] | ET2024-17 pp.25-28 |
| MI | 2023-03-06 13:54 |
Okinawa | OKINAWA SEINENKAIKAN (Okinawa, Online) (Primary: On-site, Secondary: Online) |
Prediction of missing tooth shape from dental 3D scan data for automated dental treatment planning Ryota Nakatani (NAIST), Yuto Masaki (NAIST/PSP), Yoshito Otake (NAIST), Tomoko Ikawa, Yuko Shigeta, Takuya Kihara, Shuji Shigemoto, Takumi Ogawa (Tsurumi Univ.), Mazen Soufi, Yoshinobu Sato (NAIST) MI2022-83 |
Although dental CAD/CAM systems have contributed to dental treatment, it is difficult for current systems to design toot... [more] | MI2022-83 pp.52-56 |
| MSS, SS | 2023-01-11 15:00 |
Osaka | (Osaka, Online) (Primary: On-site, Secondary: Online) |
Proposal of expanded STRIM and its application to a real-world dataset Taketo Nishio, Tetsuro Saeki (Yamaguchi Univ.), Yuichi Kato (Shimane Univ.) MSS2022-59 SS2022-44 |
We have previously proposed a statistical test rule induction method (STRIM), which induces the causality by if-then rul... [more] | MSS2022-59 SS2022-44 pp.84-89 |
| EA, US (Joint) |
2022-12-22 16:50 |
Hiroshima | Satellite Campus Hiroshima (Hiroshima) | [Poster Presentation]
Data augmentation method for machine learning on speech data Tsubasa Maruyama (Tokyo Tech), Tsutomu Ikegami (AIST), Toshio Endo (Tokyo Tech), Takahiro Hirofuchi (AIST) EA2022-68 |
In machine learning, data augmentation is a method to enhance the number and diversity of data by adding transformations... [more] | EA2022-68 pp.42-48 |
| MICT, MI | 2022-11-18 14:25 |
Aichi | Nagoya Institute of Technology (Aichi) | Development of a Statistical Model for Predicting Aging Change in Spine and Pelvis Based on Landmarks Detected in a Large Scale Torso CT Image Database Yuga Shimomoto, Yoshito Otake, Tomoki Hakotani, Mazen Soufi (NAIST), Hideki Shigematu (Nara Med. Univ.), Keisuke Uemura (Osaka Univ.), Masaki Takao (Ehime Univ.), Toshiaki Akashi (Juntendo Univ.), Kensaku Mori (Nagoya Univ./NII), Kento Aida (NII), Nobuhiko Sugano (Osaka Univ.), Yoshinobu Sato (NAIST) MICT2022-39 MI2022-68 |
One way to describe variations in skeletal shape is a statistical shape model (SSM), which statistically analyzes organ ... [more] | MICT2022-39 MI2022-68 pp.29-32 |
| ET, IPSJ-CLE | 2022-06-12 10:00 |
Aichi | Nagoya Institute of Technology/Online (Aichi, Online) (Primary: On-site, Secondary: Online) |
Developing teaching materials for university students for data analysis in statistical inquiry process Katsumi Yoshine (Nanzan Univ.) ET2022-7 |
While the number of universities where you can study data science is increasing, there is also a growing tendency to inc... [more] | ET2022-7 pp.26-29 |
| IT, ISEC, RCC, WBS | 2022-03-11 14:55 |
Online | Online (Online) | On Strong Converse Theorem for Distributed Hypothesis Testing Yasutada Oohama (UEC) IT2021-122 ISEC2021-87 WBS2021-90 RCC2021-97 |
In this study, we consider a communication system in which data generated at two points with correlation is separatley... [more] |
IT2021-122 ISEC2021-87 WBS2021-90 RCC2021-97 pp.228-233 |
| IBISML | 2022-01-18 13:40 |
Online | Online (Online) | More Powerful Selective Inference for K-means clustering with Application to Single Cell Analysis Mizuki Sato, Yumehiro Omori, Yu Inatsu, Ichiro Takeuchi (NITech) IBISML2021-25 |
K-means clustering is the most famous clustering method because of its simplicity, and it has been applied to a wide ran... [more] | IBISML2021-25 pp.54-60 |
| IN, IA (Joint) |
2021-12-16 15:35 |
Hiroshima | Higashi-Senda campus, Hiroshima Univ. (Hiroshima, Online) (Primary: On-site, Secondary: Online) |
[Short Paper]
Study on Performance Bottleneck Analysis of Flow-Level Information-Centric Network Simulator Inoue Shouta, Goto Keita, Soma Yamamoto, Hiroyuki Ohsaki (Kwansei Gakuin Univ.) IA2021-35 |
In recent years, ICN (Information-Centric Networking) that focuses on the data being transferred, rather than hosts exch... [more] | IA2021-35 pp.28-30 |
| R | 2021-10-22 13:50 |
Online | Online (Online) | Modeling and prediction of injury occurrences of sumo wrestlers by using Hawkes process Shuhei Ota (Kanagawa Univ.), Mitsuhiro Kimura (Hosei Univ.) R2021-30 |
In sumo wrestling, which is a Japanese traditional sport, lots of sumo wrestlers suffer from injuries through actual bou... [more] | R2021-30 pp.1-6 |
| RCS, SR, NS, SeMI, RCC (Joint) |
2021-07-16 13:00 |
Online | Online (Online) | On Time Slot Allocation Method with Statistical Channel State Information for Wireless Powered Sensor Networks Takeru Terauchi, Katsuya Suto (UEC), Masashi Wakaiki (Kobe Univ.) SR2021-36 |
Wireless power transfer via microwave is attracting interest because it solves the problem of battery of the sensors wit... [more] | SR2021-36 pp.81-86 |
| NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] | 2021-06-28 16:10 |
Online | Online (Online) | More Powerful and General Selective Inference for Stepwise Feature Selection using Homotopy Method Kazuya Sugiyama (Nitech), Vo Nguyen Le Duy, Ichiro Takeuchi (Nitech/RIKEN) NC2021-8 IBISML2021-8 |
Conditional selective inference (SI) has been actively studied as a new statistical inference framework for data-driven ... [more] | NC2021-8 IBISML2021-8 pp.55-61 |
| R | 2021-06-12 14:50 |
Online | Online (Zoom) (Online) | A note on a stochastic model and injury prediction for sumo wrestlers Ota Shuhei (Kanagawa Univ.), Kimura Mitsuhiro (Hosei Univ.) R2021-13 |
In sumo wrestling, one of the martial arts, sumo wrestlers have a risk of injury due to actual bouts. Sumo wrestlers suf... [more] | R2021-13 pp.13-18 |
| ET | 2021-06-05 14:00 |
Online | Online (Online) | Collecting example sentences that describe the characteristics of statistical data
-- for the purpose of improving the ability to explain statistics in text -- Katsumi Yoshine (Nanzan Univ.) ET2021-3 |
With the increasing the need for statistical, new goals for statistic learners are being considered. The new goals often... [more] | ET2021-3 pp.13-16 |
| SR | 2021-05-20 10:50 |
Online | Online (Online) | Statistic Sample Size Determination for Average Received Signal Power Using Statistical Inference Keita Katagiri, Takeo Fujii (UEC) SR2021-3 |
Nowadays, a crowdsourcing-assisted radio map has attracted attention. In crowdsourcing, distributed mobile terminals obs... [more] | SR2021-3 pp.16-23 |
| MI | 2021-03-16 09:30 |
Online | Online (Online) | Statistical modeling of pulmonary vasculatures in CT volumes using a deep generative model Yuki Saeki, Atshushi Saito (TUAT), Jean Cousty, Yukiko Kenmochi (LIGM/ UGE/ CNRS/ ESIEE Paris), Akinobu Shimizu (TUAT) MI2020-65 |
The purpose of this study is to build a statistical intensity model of pulmonary vasculatures in CT volumes. In this stu... [more] | MI2020-65 pp.80-81 |
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