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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| KBSE | 2022-03-09 16:50 |
Online | Online (Zoom) | Fairness Testing of Machine Learning Software through a Combinatorial Approach Daniel Perez Morales (AIST/Keio Univ.), Takashi Kitamura (AIST), Shingo Takada (Keio Univ.)  KBSE2021-50 |
Machine learning (ML) can be used in decision-making algorithms or classifiers. These classifiers must be tested looking... [more] | KBSE2021-50 pp.54-59 |
| ET | 2022-03-04 13:50 |
Online | Online | Proposing a Notification Strategy for a Habit-Forming Support App in Team's Use Yuuki Ueno, Yasuo Miyoshi (Kochi Univ.) ET2021-69 |
The habit-forming support app we are developing has a scheduling function and a team function. A user forms a team with ... [more] | ET2021-69 pp.103-106 |
| ET | 2022-03-04 15:20 |
Online | Online | A mixed initiative learning support system for elementary statistics based on models of learners' behavior and understanding Kanako Suzuki (Graduate Sch of Shizuoka Univ.), Tatsuhiro Konishi (Shizuoka Univ.) ET2021-75 |
In recent years, statistics has become a necessary education not only for professionals but also for various people. In ... [more] | ET2021-75 pp.135-140 |
| IE, ITS, ITE-AIT, ITE-ME, ITE-MMS [detail] | 2022-02-22 10:00 |
Online | Online | Pretext-Contrastive Learning for Self-Supervised Video Feature Learning Li Tao (UTokyo), Xueting Wang (CyberAgent, Inc.), Toshihiko Yamasaki (UTokyo) ITS2021-43 IE2021-52 |
Recently, pretext task-based methods are proposed one after another in self-supervised video feature learning. Contrasti... [more] | ITS2021-43 IE2021-52 pp.109-114 |
| RCS, SR, NS, SeMI, RCC (Joint) |
2021-07-16 09:25 |
Online | Online | Improving the Runtime Performance of Decentralized Machine Learning on Wireless Channels via Rate Adaptation Koya Sato (Tokyo Univ. of Science), Daisuke Sugimura (Tsuda Univ.) RCS2021-94 |
This paper presents a communication strategy for improving the runtime of decentralized machine learning over wireless n... [more] | RCS2021-94 pp.80-85 |
| KBSE, SWIM | 2021-05-21 11:30 |
Online | Online | Design of a Machine Learner for Adapting Competitive Game Strategies to Players' Proficiency Daisuke Takeuchi, Masami Noro, Atsushi Sawada (Nanzan Univ.) KBSE2021-2 SWIM2021-2 |
In recent, player modeling has become an important issue in the area of game AI design and many researchers and practiti... [more] | KBSE2021-2 SWIM2021-2 pp.7-12 |
| IN, NS (Joint) |
2021-03-04 11:00 |
Online | Online | Application Offloading Mechanism based on Distributed Reinforcement Learning in MEC Environment Soh Takamura, Takao Kondo, Fumio Teraoka (Keio Univ.) IN2020-67 |
This paper proposes a mechanism for determining the offloading strategy of an application running on a User Equipment (U... [more] | IN2020-67 pp.79-84 |
| NC, MBE (Joint) |
2021-03-04 16:50 |
Online | Online | A3C with Deterministic Policy Gradient Yu Takahagi, Yukari Yamauchi (Nihon Univ.) NC2020-63 |
Mnih et al. proposed a learning method called Asynchronous Advantage Actor-Critic (A3C). This method explores asynchrono... [more] | NC2020-63 pp.117-120 |
| IBISML | 2021-03-03 11:15 |
Online | Online | IBISML2020-46 |
Developing a profitable trading strategy is a central problem in the financial industry. In this presentation, we develo... [more] | IBISML2020-46 p.38 |
| NS, NWS (Joint) |
2021-01-22 15:45 |
Online | Online | A Study of Caching Policy with Cache Hit Prediction for User Generated Video Meguru Yamazaki, Miki Yamamoto (Kansai Univ.) NS2020-121 |
With wide deployment of video platforms on which users can upload their generating videos, such as YouTube and niconico,... [more] | NS2020-121 pp.66-69 |
| PRMU | 2020-12-17 14:40 |
Online | Online | Belonging Network
-- Few-shot One-class Image Classification for Classes with Various Distributions -- Takumi Ohkuma, Hideki Nakayama (UT) PRMU2020-44 |
Few-shot one-class image classification is the task of recognizing a particular class while rejecting test images that d... [more] | PRMU2020-44 pp.36-41 |
| AI | 2020-12-11 09:05 |
Shizuoka | Online and HAMAMATSU ACT CITY (Primary: On-site, Secondary: Online) |
An Automated Driving Strategy for Microscopic Road Traffic Using Multi-Agent Deep Reinforcement Learning Ryota Suwa, Toshiharu Sugawara (Waseda Univ.) AI2020-7 |
This study proposes a method for interaction-aware automated driving in microscopic road traffic simulations using multi... [more] | AI2020-7 pp.34-38 |
| WIT | 2020-09-08 14:45 |
Online | Online | Sign Language Learning Support System
-- Proposal of Functions as Clearly Indicate Learning Points using Sign Keyframe -- Sho Inooka (SIT), Ken Tsutsuguchi (Sojo Univ.), Shunichi Yonemura (SIT) WIT2020-8 |
In case of novices learn sign language in self-study, they use books and videos as learning materials. Although illustra... [more] | WIT2020-8 pp.15-20 |
| IA, SITE, IPSJ-IOT [detail] | 2020-03-02 16:55 |
Online | Online | The design of the sample policy for utilizing educational data Hiroshi Ueda (Hosei Univ.), Hiroaki Ogata (Kyoto Univ.), Tsuneo Yamada (The Open Univ. of Japan) SITE2019-93 IA2019-71 |
We have been studied about the policy for educational data usage for research including Learning Analytics. Because ther... [more] | SITE2019-93 IA2019-71 pp.51-57 |
| COMP | 2020-03-01 16:50 |
Tokyo | The University of Electro-Communications (Cancelled but technical report was issued) |
Online Learning for A Repeated Markovian Game with 2 States Shangtong Wang, Shuji Kijima (Kyushu Univ.) COMP2019-55 |
We consider a new problem of learning in repeated games. In our model, the players play on one of the several game matri... [more] | COMP2019-55 pp.65-68 |
| MI | 2020-01-29 13:20 |
Okinawa | OKINAWAKEN SEINENKAIKAN | Imbalanced Subarachnoid Hemorrhage data automatic detection by using SMOTE algorithm based on deep learning Zhongyang Lu, Masahiro Oda, Yuichiro Hayashi, Hayato Ito (Nagoya Univ), Takeyuki Watadani, Osamu Abe (Department of Radiology,The Univ of Tokyo Hospital), Masahiro Hashimoto, Masahiro Jinzaki (Department of Radiology,Keio Univ School of Medicine), Kensaku Mori (Nagoya Univ) MI2019-75 |
Based on deep learning techniques, the performance of image classification has made significant progress. Especially in ... [more] | MI2019-75 pp.47-52 |
| NLP, NC (Joint) |
2020-01-25 16:25 |
Okinawa | Miyakojima Marine Terminal | Reinforcement learning of communication strategy between players of the game of Contract Bridge Yotaro Yamaguchi, Sotetsu Koyamada, Ken Nakae, Shin Ishii (Kyoto Univ.) NLP2019-111 |
Contract bridge (bridge) is a card game in which four players are divided into two teams and cooperate with a partner to... [more] | NLP2019-111 pp.131-134 |
| RISING (2nd) |
2019-11-26 14:10 |
Tokyo | Fukutake Learning Theater, Hongo Campus, Univ. Tokyo | [Poster Presentation]
A Demonstrative Study on the Throughput Improvement for Store-Carry-Forward Data Delivery
-- An Approach of Vehicle Mobility Prediction Based on Deep Learning -- Yoshito Watanabe, Wei Liu, Yozo Shoji (NICT) |
A store-carry-forward (SCF) strategy is one of the data delivery methods by the physical movement of nodes and has the p... [more] | |
| PRMU, CNR | 2019-02-28 13:30 |
Tokushima | A teachable agent asking question: using the learning-by-teaching strategy Le Ray Briac, Sono Taichi, Imai Michita (Keio Univ.) PRMU2018-115 CNR2018-38 |
Care receiving robots, care receiving agents and teachable agents are based on the proof that people can learn by teachi... [more] | PRMU2018-115 CNR2018-38 pp.7-10 |
|
| SP | 2019-01-27 11:30 |
Ishikawa | Kanazawa-Harmonie | Multimodal Data Augmentation for Visual Speech Recognition using Deep Canonical Correlation Analysis Masaki Shimonishi, Satoshi Tamura, Satoru Hayamizu (Gifu University) SP2018-60 |
This paper proposes ta new data augmentation strategy for deep learning, in which feature vectors in one modality can be... [more] | SP2018-60 pp.41-45 |
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