| IEICE Technical Committee Submission System Conference Schedule |
Online Proceedings [Sign in] Tech. Rep. Archives |
All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| SeMI | 2022-01-20 15:00 |
Nagano | (Primary: On-site, Secondary: Online) |
[Short Paper]
Evaluation of Few Round Training with Distillation-Based Semi-Supervised Federated Learning Yuki Yoshida (Tokyo Tech), Sohei Itahara (Kyoto Univ.), Takayuki Nishio (Tokyo Tech)  SeMI2021-65 |
This paper studies how to reduce the number of rounds in model training using Distillation-based Semi-supervised federat... [more] | SeMI2021-65 pp.48-50 |
| SeMI | 2022-01-20 15:10 |
Nagano | (Primary: On-site, Secondary: Online) |
[Short Paper]
A Study of Joint Control of Machine Learning Model and Wireless LAN Parameters in Split inference by Reinforcement Learning Kojin Yorita (Tokyo Tech.), Sohei Itahara (Kyoto Univ.), Takayuki Nishio (Tokyo Tech.), Daiki Yoda, Toshihisa Nabetani (Toshiba) SeMI2021-66 |
Distributed inference (DI) enables machine learning (ML) inference with a deep neural network on resource-constrained de... [more] | SeMI2021-66 pp.51-54 |
| SeMI | 2022-01-20 15:20 |
Nagano | (Primary: On-site, Secondary: Online) |
[Short Paper]
A Study of Beamforming Feedback-based Model-driven Angle of Departure Estimation Sohei Itahara (Kyoto Univ.), Takayuki Nishio (Kyoto Univ./Tokyo Tech.), Koji Yamamoto (Kyoto Univ.) SeMI2021-68 |
This paper introduces the angle of departure (AoD) estimation method [1] using the multiple signal classification (MUSIC... [more] | SeMI2021-68 pp.59-61 |
| SeMI | 2022-01-20 15:30 |
Nagano | (Primary: On-site, Secondary: Online) |
[Short Paper]
A Method for Improving Accuracy of Wireless Sensing with Bi-directional Beamforming Feedback Matrices Sota Kondo, Souhei Itahara, Kota Yamashita, Koji Yamamoto (Kyoto Univ.), Yusuke Koda (Univ. Oulu), Takayuki Nishio (Kyoto University/Tokyo Tech.), Akihito Taya (Kyoto Univ./Aoyama Gakuin Univ.) SeMI2021-69 |
[more] | SeMI2021-69 pp.62-64 |
| SeMI | 2022-01-21 09:50 |
Nagano | (Primary: On-site, Secondary: Online) |
[Short Paper]
A Study of Computer Vision-aided Single-antenna and Single-anchor RSSI Localization Considering Movable Obstructions Tomoya Sunami, Sohei Itahara (Kyoto Univ.), Yusuke Koda (Oulu Univ.), Takayuki Nishio (Kyoto Univ./Tokyo Tech.), Koji Yamamoto (Kyoto Univ.) SeMI2021-75 |
This paper shows the feasibility of single-antenna and single-RF (radio frequency)-anchor received power strength indica... [more] | SeMI2021-75 pp.89-91 |
| SRW, SeMI, CNR (Joint) |
2021-11-26 15:00 |
Tokyo | Kikai-Shinko-Kaikan Bldg. (Primary: On-site, Secondary: Online) |
[Poster Presentation]
Frame-Capture-Based CSI Recomposition Pertaining to Firmware-Agnostic WiFi Sensing Ryosuke Hanahara, Sohei Itahara, Kota Yamashita (Kyoto Univ.), Yusuke Koda (Univ. Oulu), Akihito Taya (Kyoto Univ./Aoyama Gakuin Univ.), Takayuki Nishio (Kyoto Univ./Tokyo Tech.), Koji Yamamoto (Kyoto Univ.) SRW2021-48 SeMI2021-47 CNR2021-22 |
This paper presents an estimation method of channel state information (CSI) matrices using corresponding beamforming fee... [more] | SRW2021-48 SeMI2021-47 CNR2021-22 pp.71-73(SRW), pp.58-60(SeMI), pp.48-50(CNR) |
| SeMI | 2021-01-20 13:20 |
Online | Online | A Study of Online Training Method for Image-based Wireless Link Quality Prediction Sohei Itahara (Kyoto Univ), Takayuki Nishio (Tokyo Tech), Masahiro Morikura, Koji Yamamoto (Kyoto Univ) SeMI2020-44 |
Machine-learning-based prediction of future wireless link quality is an emerging technique that can potentially improve ... [more] | SeMI2020-44 pp.7-9 |
| SeMI | 2020-01-31 10:00 |
Kagawa | [Poster Presentation]
Communication-Efficient Federated Learning Using Non-Labeled Data Souhei Itahara, Takayuki Nishio, Masahiro Morikura, Koji Yamamoto (Kyoto Univ) SeMI2019-109 |
Federated learning (FL) is a machine learning setting where many mobile devices collaboratively train a machine learning... [more] | SeMI2019-109 pp.47-48 |
|
| RISING (2nd) |
2019-11-26 14:10 |
Tokyo | Fukutake Learning Theater, Hongo Campus, Univ. Tokyo | [Poster Presentation]
A Study for Knowlage Distillation Based Semi-Supervised Federated Learning with Low Communication Cost Sohei Itahara, Takayuki Nishio, Masahiro Morikura, Koji Yamamoto (Kyoto Univ) |
Federated Learning is a decentralized learning mechanism, which enables to train machine learning (ML) model using the r... [more] | |
[Return to Top Page]