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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 45  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
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)
 [more]
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]
SeMI, RCS, NS, SR, RCC
(Joint)
2019-07-11
10:40
Osaka I-Site Nanba(Osaka) [Poster Presentation] A Study on Efficient Secure Routing Protocol based on AODV for Large Scale Ad Hoc Networks
Yuma Shibasaki, Koya Sato, Keiichi Iwamura (TUS) RCC2019-31 NS2019-67 RCS2019-124 SR2019-43 SeMI2019-40
This paper proposes a secure routing protocol based on Ad hoc On-demand Distance Vector (AODV) that achieves both securi... [more] RCC2019-31 NS2019-67 RCS2019-124 SR2019-43 SeMI2019-40
pp.101-106(RCC), pp.127-132(NS), pp.123-128(RCS), pp.133-138(SR), pp.115-120(SeMI)
RCS, SR, SRW
(Joint)
2019-03-06
15:40
Kanagawa YRP [Invited Lecture] Spectrum Sharing based on Radio Environment Map: Theory and Open Issues
Koya Sato (Tokyo Univ. of Science) SR2018-127
This paper summarizes the radio environment map (REM) for spatial spectrum sharing. REM contains spatial distribution of... [more] SR2018-127
pp.43-49
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