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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| SR | 2024-05-21 10:45 |
Kagoshima | Yokacenter (Kagoshima) (Primary: On-site, Secondary: Online) |
[Short Paper]
A Study on Low-Complexity Simulation Framework for Large-Scale Channel Knowledge Maps with Spatial Correlation Koya Sato, Katsuya Suto (UEC) |
(To be available after the conference date) [more] | |
| RCS | 2023-10-20 14:35 |
Kagawa | Kagawa University (Saiwai-cho Campus), and online (Primary: On-site, Secondary: Online) |
[Invited Lecture]
Research Trends of Radio Map Applications for the 6G Era Koya Sato (UEC)  RCS2023-147 |
A radio map is a tool for visualizing received signal power values over a spatial domain. Over the last decade, there ha... [more] | RCS2023-147 p.89 |
| SeMI, RCS, RCC, NS, SR (Joint) |
2023-07-12 13:55 |
Osaka | Osaka University Nakanoshima Center + Online (Primary: On-site, Secondary: Online) |
Radio Propagation Graph Representation Learning Katsuya Suto, Shinsuke Bannai, Koya Sato, Takeo Fujii (UEC) SR2023-29 |
In the paper, we propose a novel concept of data-driven radio propagation estimation, referred to as radio propagation g... [more] | SR2023-29 pp.19-24 |
| SR | 2023-05-12 10:25 |
Hokkaido | Center of lifelong learning Kiran (Higashi Muroran) (Primary: On-site, Secondary: Online) |
A Study on Adaptive Client/Miner Selection for Fast and Accurate Blockchain-Decentralized Federated Learning Yuta Tomimasu, Koya Sato (UEC) SR2023-17 |
Decentralized federative learning with blockchain is a learning method in which the model in federated learning is manag... [more] | SR2023-17 pp.83-88 |
| SR | 2023-05-12 13:55 |
Hokkaido | Center of lifelong learning Kiran (Higashi Muroran) (Primary: On-site, Secondary: Online) |
[Invited Talk]
Federated Learning-Inspired Gaussian Process Regression: Low Latency Design and Its Application to Radio Map Construction Koya Sato (UEC) SR2023-20 |
Gaussian process regression (GPR) is a non-parametric method that optimizes regression analysis for Gaussian process dat... [more] | SR2023-20 p.91 |
| RCS, SR, SRW (Joint) |
2023-03-01 13:55 |
Tokyo | Tokyo Institute of Technology, and Online (Primary: On-site, Secondary: Online) |
[Invited Lecture]
Modeling of Geospatial Data for Digital Twin Wireless Systems Koya Sato (UEC) SR2022-83 |
Over the last decade, there has been a wide range of discussions on digital-twin wireless systems. The digital-twin wire... [more] | SR2022-83 p.3 |
| SR, UWT (Joint) |
2023-01-27 10:55 |
Tokyo | Takanawa Campus, Tokai Univ. (Primary: On-site, Secondary: Online) |
A Study on Reinforcement Learning-Based Adaptive Random Walk SGD for Attack-Resilient Decentralized Federated Learning Masakazu Okamoto (Tokyo Univ. of Science), Koya Sato (UEC), Keiichi Iwamura (Tokyo Univ. of Science) SR2022-76 |
[more] | SR2022-76 pp.20-27 |
| NS, ICM, CQ, NV (Joint) |
2022-11-24 09:55 |
Fukuoka | Humanities and Social Sciences Center, Fukuoka Univ. + Online (Primary: On-site, Secondary: Online) |
Highly Accurate Privacy-Enhanced Federated Learning Using Data On The Server Yuta Kakizaki (TUS), Koya Sato (UEC), Keiichi Iwamura (TUS) NS2022-100 |
Federated learning is a cooperative machine learning approach that prohibits disclosing training data from distributed d... [more] | NS2022-100 pp.1-6 |
| IT, EMM | 2022-05-18 14:20 |
Gifu | Gifu University (Primary: On-site, Secondary: Online) |
[Invited Talk]
Decentralized Federated Learning: Fundamentals, Research Trends and Open Issues in Wireless Channels Koya Sato (UEC) IT2022-14 EMM2022-14 |
The expansion of machine learning applications has raised novel concerns, such as data privacy and communication costs. ... [more] | IT2022-14 EMM2022-14 p.73 |
| SR | 2022-05-13 10:30 |
Tokyo | NICT Koganei (Primary: On-site, Secondary: Online) |
[Short Paper]
On Automated Indoor Wireless Simulation with Image Sensor and 3D Reconstruction Koya Sato (UEC), Norisato Suga (SIT), Yoshihiro Maeda (Tokyo Univ. of Science) SR2022-12 |
[more] | SR2022-12 pp.55-57 |
| RCS, SR, SRW (Joint) |
2022-03-02 13:05 |
Online | Online | [Invited Lecture]
Radio Map Extrapolation Using Compensated Empirical CDF under Interference-Limited Observations Keita Katagiri, Koya Sato (UEC), Kei Inage (TMCIT), Takeo Fujii (UEC) SR2021-92 |
[more] | SR2021-92 pp.28-35 |
| RCS, SR, SRW (Joint) |
2022-03-04 09:45 |
Online | Online | [Short Paper]
On Implementation of Radio Propagation Simulator with Open 3D City Models Koya Sato (UEC) SR2021-113 |
In radio propagation simulations, the acquisition of precise information such as structures and topography is a signific... [more] | SR2021-113 pp.121-123 |
| SIP | 2021-08-23 14:50 |
Online | Online | [Invited Talk]
Visualizing Wireless Environments: An Introduction of Spatial Statistics and Its Extensions to Multi-Dimensional Interpolation Koya Sato (Tokyo Univ. of Science) SIP2021-30 |
The radio map construction has been attracting attention. This technology visualizes the state of the wireless environme... [more] | SIP2021-30 pp.12-17 |
| 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 |
| RCS, SR, NS, SeMI, RCC (Joint) |
2021-07-16 10:55 |
Online | Online | A Study on Decentralized Machine Learning with Differential Privacy based on Input Perturbation Masakazu Okamoto, Koya Sato, Keiichi Iwamura (Tokyo Univ. of Science) SR2021-34 |
Distributed machine learning eliminates the need for users to disclose their data to the out of the terminal since train... [more] | SR2021-34 pp.67-72 |
| RCS, SR, NS, SeMI, RCC (Joint) |
2021-07-16 13:25 |
Online | Online | An Evaluation of Learning Accuracy in Federated Learning with Local Differential Privacy Yuta Kakizaki, Koya Sato, Keiichi Iwamura (Tokyo Univ. of Science) SR2021-37 |
In federated learning, where each device learns cooperatively without disclosing the training data, the privacy level ca... [more] | SR2021-37 pp.87-93 |
| SR | 2020-11-20 10:00 |
Online | Online | Compensation of Clutter Loss Considering Antenna Height Difference and Dominant Path for Spectrum Sharing Sunao Miyamoto, Keita Katagiri (UEC), Koya Sato (TUS), Koichi Adachi, Takeo Fujii (UEC) SR2020-39 |
In recent years, spectrum sharing technology is attracting attention to solve the problem of spectrum shortage. In order... [more] | SR2020-39 pp.108-113 |
| SR | 2020-11-20 14:05 |
Online | Online | [Panel Discussion]
Data-Driven Radio Propagation Estimation for Spectrum Sharing: Trends and Challenges Koya Sato (TUS) SR2020-45 |
In the field of spectrum sharing, spectrum database has been recognized as a practical enabler for estimating and managi... [more] | SR2020-45 pp.146-151 |
| SR, NS, SeMI, RCC, RCS (Joint) |
2020-07-10 11:35 |
Online | Online | Experimental Verification of Shadowing Classification for Measurement-based Spectrum Database Keita Katagiri (UEC), Koya Sato (TUS), Kei Inage (TMCIT), Takeo Fujii (UEC) SR2020-20 |
As a hybrid estimation method of the radio environment, we have proposed a shadowing classifier. In the shadowing classi... [more] | SR2020-20 pp.63-70 |
| RISING (2nd) |
2019-11-27 13:55 |
Tokyo | Fukutake Learning Theater, Hongo Campus, Univ. Tokyo | [Poster Presentation]
Clustering of Signal Power Distribution Toward Low Storage Crowdsourced Spectrum Database Yoji Uesugi, Keita Katagiri (UEC), Koya Sato (TUS), Takeo Fujii (TMCIT), Takeo Fujii (UEC) |
[more] | |
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