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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| RCS | 2024-06-20 09:30 |
Okinawa | (Primary: On-site, Secondary: Online) |
[more] | ||
| NS, PN, OCS (Joint) |
2024-06-07 09:25 |
Nagasaki | (Primary: On-site, Secondary: Online) |
Study on Disaggregated Computer Architecture Based on NVMe-over-Fabrics for Deep Learning Tasks Tatsuki Oyama, Kohei Shiomoto (TCU) |
(To be available after the conference date) [more] | |
| EA | 2024-05-22 13:50 |
Online | Online | Determined BSS based on the proximal average of IVA and DNNs Kazuki Matsumoto (Waseda Univ.), Koki Yamada, Kohei Yatabe (TUAT) |
(To be available after the conference date) [more] | |
| CQ, CS (Joint) |
2024-05-16 14:55 |
Aichi | (Primary: On-site, Secondary: Online) |
Force Adjustment Control in Cooperative Work between Remote Robot Systems with Force Feedback
-- Application of Reinforcement Learning -- Hitoshi Ohnishi (OUJ), Hiroya Kato, Yutaka Ishibashi (Nagoya Institute of Technology), Pingguo Huang (Gifu Shotoku Gakuen Univ.) |
(To be available after the conference date) [more] | |
| ET | 2024-03-03 13:45 |
Miyazaki | Miyazaki University | Examination on Adaptive Questions in Braille Learning using Multi-Armed Bandits Algorithm Yasuhisa Okazaki, Jevri Tri Ardiansah (Saga Univ.)  ET2023-70 |
In adaptive learning, it is desirable to appropriately present the next topic for each learner to learn. A typical metho... [more] | ET2023-70 pp.110-115 |
| AI | 2024-03-01 13:40 |
Aichi | Room0221, Bldg.2-C, Nagoya Institute of Technology | Applying Graph Neural Networks and Reinforcement Learning to the Multiple Depot-Multiple Traveling Salesman Problem Dongyeop Kim, Toshihiro Matsui (NITech) AI2023-39 |
In this study, we introduce a method combining Graph Neural Networks (GNN) and reinforcement learning for the Multiple D... [more] | AI2023-39 pp.13-18 |
| AI | 2024-03-01 15:00 |
Aichi | Room0221, Bldg.2-C, Nagoya Institute of Technology | Performance Improvement for Mobile Edge Computing with Multi-Agent Deep Reinforcement Learning Kohei Suzuki, Toshiharu Sugawara (Waseda Univ.) AI2023-42 |
In this paper, we propose a method for mobile edge computing using unmanned aerial vehicles (UAVs) to improve both the n... [more] | AI2023-42 pp.31-36 |
| NS, IN (Joint) |
2024-03-01 11:35 |
Okinawa | Okinawa Convention Center | Application of a Deep Reinforcement Learning Algorithm to Virtual Machine Migration Control in Multi-Stage Information Processing Systems Yuki Kojitani (Okayama Univ.), Kazutoshi Nakane (Nagoya Univ.), Yuya Tarutani (Okayama Univ.), Celimuge Wu (UEC), Yusheng Ji (NII), Tokumi Yokohira (Okayama Univ.), Tutomu Murase (Nagoya Univ.), Yukinobu Fukushima (Okayama Univ.) IN2023-87 |
This paper tackles a virtual machine (VM) migration control problem to maximize the progress (accuracy) of information p... [more] | IN2023-87 pp.130-135 |
| ITS, IE, ITE-MMS, ITE-ME, ITE-AIT [detail] | 2024-02-19 11:00 |
Hokkaido | Hokkaido Univ. | Improving Adversarial Robustness in Continual Learning Koki Mukai, Soichiro Kumano (UTokyo), Nicolas Michel (UGE/CNRS/LIGM), Ling Xiao, Toshihiko Yamasaki (UTokyo) ITS2023-48 IE2023-37 |
The goal of continual learning is to prevent catastrophic forgetting. However, few studies have simultaneously considere... [more] | ITS2023-48 IE2023-37 pp.13-18 |
| SS, MSS | 2024-01-18 11:30 |
Ishikawa | (Primary: On-site, Secondary: Online) |
Deep Reinforcement Learning Using LMM's Studying Papers and Intrinsic Rewards Sota Nagano, Satoshi Yamane (Kanazawa Univ.) MSS2023-64 SS2023-43 |
Research combining deep reinforcement learning with a large language model (LLM) produced high scores even for open-worl... [more] | MSS2023-64 SS2023-43 pp.70-75 |
| DE, IPSJ-DBS | 2023-12-26 14:00 |
Tokyo | Institute of Industrial Science, The University of Tokyo | Interpretation of unsupervised clustering based on XAI Yu Sasaki, Fumiaki Saitoh (CIT) DE2023-28 |
Explainable Artificial Intelligence (XAI) aims to introduce transparency and interpretability into the decision-making o... [more] | DE2023-28 pp.1-6 |
| DE, IPSJ-DBS | 2023-12-26 14:20 |
Tokyo | Institute of Industrial Science, The University of Tokyo | A study on selective reuse of local policies in transfer learning agents Hiroya Hamada, Fumiaki Saitoh (CIT) DE2023-29 |
In recent years, reinforcement learning has gained attention for its application in acquiring AI behaviors. One challeng... [more] | DE2023-29 pp.7-11 |
| HCGSYMPO (2nd) |
2023-12-11 - 2023-12-13 |
Fukuoka | Asia pacific Import Mart (Kitakyushu) (Primary: On-site, Secondary: Online) |
Gaze features representing anticipatory gaze and machine learning models for predicting Self-Efficacy
-- From data in use of a rotational transformation mouse -- Yuka Hayakawa, Saki Tanaka, Airi Tsuji (TUAT), Junichi Yamamoto (TMU), Kaori Fujinami (TUAT) |
Self-efficacy is the degree of confidence in one's ability to perform a behavior, and has been attempted to apply to pr... [more] | |
| SIS | 2023-12-07 14:40 |
Aichi | Sakurayama Campus, Nagoya City University (Primary: On-site, Secondary: Online) |
Transfer Learning-Based Detection of Swallowing Sounds and its Application for Swallowing Measurement Reoto Nishijima, Ryoichi Miyazaki (NITTC) SIS2023-29 |
Dysphagia is a problem with the act of swallowing food or drink. Dysphagia can cause aspiration, in which food or drink ... [more] | SIS2023-29 pp.31-36 |
| SIS | 2023-12-08 14:10 |
Aichi | Sakurayama Campus, Nagoya City University (Primary: On-site, Secondary: Online) |
Improvement of Multi-task Training for Detection of Calcification Regions in Dental Panoramic Radiographs Kazuki Iwasaki, Mitsuji Muneyasu, Taito Murano, Soh Yoshida, Akira Asano (Kansai Univ.), Nanae Dewake, Nobuo Yoshinari (Matsumoto Dental Univ.), Keiichi Uchida (Matsumoto Dental Univ. Hospital) SIS2023-43 |
Carotid arteries on dental panoramic radiographs may show areas of calcification, a sign of vascular disease. Detection ... [more] | SIS2023-43 pp.105-110 |
| NC, MBE (Joint) |
2023-11-27 10:30 |
Osaka | Kindai Univ. (Primary: On-site, Secondary: Online) |
Improving the reproduction of animal intelligence using reinforcement learning with World Model Takumi Fukaya, Hirokazu Tanaka (Tokyo City Univ.) NC2023-34 |
One way to evaluate artificial intelligence models that reproduce animal intelligence is to have reinforcement learning ... [more] | NC2023-34 pp.6-9 |
| NC, MBE (Joint) |
2023-10-27 13:30 |
Miyagi | Tohoku Univ. (Primary: On-site, Secondary: Online) |
Significance of single cell recording
-- Reverse engineering from supplementary motor cortex neuronal activity to reinforcement learning model -- Nao Matsumoto, Naoki M. Tamura, Hajime Mushiake (Tohoku Univ. Sch. Med.), Kazuhiro Sakamoto (TMPU) NC2023-25 |
Elucidating the regions of the brain that are active in a given cognitive activity is an important mission in neuroscien... [more] | NC2023-25 pp.1-5 |
| NC, MBE (Joint) |
2023-10-28 10:05 |
Miyagi | Tohoku Univ. (Primary: On-site, Secondary: Online) |
Research on Screening for Dementia by Analyzing Eye Gaze Data Yuji Maegawa, Yutaka Kawaguchi (Kobe Univ.), Mamoru Hiroe (Osaka Seikei Univ./Kobe Univ.), Maki Uchimura (Kobe Univ.), Minoru Nakayama (Tokyo Tech), Zheng Yujia, Yuma Sonoda, Hisatomo Kowa, Takashi Nagamatsu (Kobe Univ.) MBE2023-24 |
Current screening tests for dementia are time-consuming and have other problems, and the development of simpler tests is... [more] | MBE2023-24 pp.9-14 |
| TL | 2023-09-30 12:40 |
Tokyo | University of Tokyo | Shared Neural Representations of Semantic Categories for Images and Words
-- A Study Using Decoding Analysis of MEG Data -- Kai Nakajima, Jion Tominaga, Dmitry Patashov (Waseda Univ.), Keita Tanaka, Akihiko Tsukahara (TDU), Hiroki Miyanaga, Shoji Tsunematsu (SHI), Rieko Osu, Hiromu Sakai (Waseda Univ.) TL2023-16 |
Even when objects are presented as words or images, humans can identify their semantic categories. The extent to which t... [more] | TL2023-16 pp.3-8 |
| DE, IPSJ-DBS, IPSJ-IFAT [detail] | 2023-09-21 15:00 |
Fukuoka | Kitakyushu International Conference Center | Analysis of subtasks for improving the detection accuracy of offensive tweets in multitask learning Ryoichi Sawada, Yu Suzuki (Gifu) DE2023-14 |
There are studies on detecting offensive tweets, but there is a need to further improve the accuracy.One method to impro... [more] | DE2023-14 pp.19-24 |
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