| 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 # | |
| VLD, HWS, ICD | 2024-03-01 14:25 |
Okinawa | (Primary: On-site, Secondary: Online) |
Modeling of Thin-Film Ferroelectric Memcapacitors Based on Gaussian Process Regression and its evaluation Ryoga Urata (KIT), Taiyo Shinoda, Mutsumi Kimura (Ryukoku Univ.), Michihiro Shintani (KIT)  VLD2023-128 HWS2023-88 ICD2023-117 |
Ferroelectric memcapacitors using thin-film materials are attracting attention as a circuit element that can realize sum... [more] | VLD2023-128 HWS2023-88 ICD2023-117 pp.151-156 |
| SANE | 2023-12-08 13:50 |
Overseas | Surakarta, Indonesia (Primary: On-site, Secondary: Online) |
Finger Position Detection Using Multitask Gaussian Process Regression on Noncontact Control Panels Takayuki Kitamura, Shingo Yamaura, Kengo Nishimoto, Tadashi Oshima (MELCO) SANE2023-81 |
In recent years, the development of transparent antennas for fifth-generation mobile communication systems has progresse... [more] | SANE2023-81 pp.116-121 |
| NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] | 2023-06-29 14:20 |
Okinawa | OIST Conference Center (Primary: On-site, Secondary: Online) |
Crystal structure X-ray absorption spectrum prediction and valence ratio estimation based on Gaussian process regression Takumi Iwashita, Haruki Hirai, Ryo Kobayashi, Tomoyuki Tamura, Masayuki Karasuyama (NIT) NC2023-3 IBISML2023-3 |
X-ray absorption spectra are known as a useful experimental measurement technique for crystal structure analysis. Spectr... [more] | NC2023-3 IBISML2023-3 pp.17-24 |
| SRW | 2023-06-12 11:10 |
Tokyo | Kikai-Shinko-Kaikan Bldg. (Primary: On-site, Secondary: Online) |
[Invited Lecture]
Channel Prediction for Overhead Reduction of Channel Estimation in IRS-Assisted Wireless Communication Systems Norisato Suga (ATR/SIT), Kazuto Yano (ATR), Yafei Hou (ATR/Okayama Univ.), Toshikazu Sakano (ATR) SRW2023-4 |
The use of intelligent reflecting surface (IRS), which is a surface arrangement of elements that can control the phase o... [more] | SRW2023-4 pp.19-24 |
| 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 |
| IMQ, IE, MVE, CQ (Joint) [detail] |
2023-03-15 13:15 |
Okinawa | Okinawaken Seinenkaikan (Naha-shi) (Primary: On-site, Secondary: Online) |
A Study on Quality Degradation Estimation Model for Transcoding Videos Ryo Saimi, Takanori Hayashi (Hiroshima Institute of Technology) CQ2022-86 |
To provide video delivery services with comfortable quality, it is important to design applications and networks based o... [more] | CQ2022-86 pp.37-42 |
| SANE, SAT (Joint) |
2023-03-03 09:30 |
Okinawa | (Primary: On-site, Secondary: Online) |
Simulation Study on Finger Position Detection Method Using Gaussian Process Regression on Non-contact Control Panels Takayuki Kitamura, Tomoya Yamaoka, Satoshi Kageme (MELCO) SANE2022-114 |
In recent years, development of transparent antennas for 5G mobile communications has been progressing, in which transpa... [more] | SANE2022-114 pp.86-90 |
| HWS, VLD | 2023-03-01 11:50 |
Okinawa | (Primary: On-site, Secondary: Online) |
Acceleration of Memristor Modeling Based on Machine Learning Using Gaussian Process Yuta Shintani, Michiko Inoue (Naist), Michihiro Shintani (Kyoto Institute of Technology) VLD2022-75 HWS2022-46 |
There has been a great deal of research into the development of domain-specific circuits for multiply-and-accumulate pro... [more] | VLD2022-75 HWS2022-46 pp.13-18 |
| NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] | 2022-06-27 14:25 |
Okinawa | (Primary: On-site, Secondary: Online) |
A Bagging Method to Improve the Accuracy of Gaussian Process Regression for Neural Architecture Search Rion Hada, Masao Okita, Fumihiko Ino (Osaka Univ.) NC2022-2 IBISML2022-2 |
The goal of this study is to improve performance estimation for neural network architectures in neural architecture sear... [more] | NC2022-2 IBISML2022-2 pp.6-13 |
| VLD, HWS [detail] | 2022-03-08 09:55 |
Online | Online | Wafer-Level Characteristic Variation Modeling with Considering Discontinuous Effect Caused by Manufacturing Equipment Takuma Nagao (National Institute of Technology (KOSEN)), Michihiro Shintani (Nara Institute of Science and Technology), Ken'ichi Yamaguchi, Hiroshi Iwata (National Institute of Technology (KOSEN)), Tomoki Nakamura, Masuo Kajiyama, Makoto Eiki (SCK), Michiko Inoue (Nara Institute of Science and Technology) VLD2021-92 HWS2021-69 |
Statistical methods for predicting the performance of large-scale integrated circuits (LSIs) manufactured on a wafer are... [more] | VLD2021-92 HWS2021-69 pp.87-92 |
| SANE | 2022-01-18 11:30 |
Tokyo | ENRI (Primary: On-site, Secondary: Online) |
Improvements of Trajectory Estimation for Commercial Aircraft by using Gaussian Process Regression
-- Modeling Calibrated Airspeed of Descending Aircraft in Terminal Airspace -- Daichi Toratani (MPAT, ENRI) SANE2021-86 |
Trajectory prediction technique for commercial aircraft is an important element of air traffic control. Since the trajec... [more] | SANE2021-86 pp.19-24 |
| NLP, CCS | 2021-06-11 10:50 |
Online | Online | A Study on Prediction of Synchrophasor Time-Series Data of In-Campus Distribution Voltage Using Gaussian Process Regression Munetaka Noguchi (Osaka Pref Univ.), Yoshihiko Susuki (Osaka Pref Univ./JST), Atsushi Ishigame (Osaka Pref Univ.) NLP2021-3 CCS2021-3 |
Due to recent penetration of distributed energy resources, dynamics of power distribution systems have been complicated ... [more] | NLP2021-3 CCS2021-3 pp.10-13 |
| AI | 2019-09-14 09:55 |
Kagoshima | Fishing Spot Estimation by Using Sea Temperature Pattern Takumi Shimura, Motoharu Sonogashira, Hidekazu Kasahara, Masaaki Iiyama (Kyoto Univ.) AI2019-27 |
(To be available after the conference date) [more] | AI2019-27 pp.45-49 |
|
| SP, ASJ-H | 2018-01-20 13:25 |
Tokyo | The University of Tokyo | A study on statistical speech synthesis based on GP-DNN hybrid model Tomoki Koriyama, Takao Kobayashi (Tokyo Tech) SP2017-67 |
We propose a novel approach to Gaussian process regression (GPR)-based speech synthesis in this paper. Since the conve... [more] |
SP2017-67 pp.5-10 |
| NC, IPSJ-BIO, IBISML, IPSJ-MPS (Joint) [detail] |
2015-06-25 15:20 |
Okinawa | Okinawa Institute of Science and Technology | A study on prediction of contact force between a large DoFs robot with backdrivability and a soft object Yuya Okadome, Yutaka Nakamura, Yoshihiro Nakata, Hiroshi Ishiguro (Osaka Univ.) NC2015-8 |
Robots must cope with various disturbances such as collision with obstacle in a real environment. A bio-inspired robot ... [more] | NC2015-8 pp.77-82 |
| PRMU, IPSJ-CVIM, MVE [detail] | 2015-01-22 15:50 |
Nara | Covariance matrix estimation for multivariate Gaussian process regression Yuki Matsumura, Toshikazu Wada (Wakayama Univ.) PRMU2014-98 MVE2014-60 |
Gaussian process regression is a nonlinear regression that estimates the expected value of the of the output and its var... [more] | PRMU2014-98 MVE2014-60 pp.117-122 |
|
| MoNA, IPSJ-DPS, IPSJ-MBL | 2013-05-23 09:55 |
Okinawa | Ishigaki City Hall | The proposal of multiplex sound analysis scheme based on spectrum basis using Gauss process regression model Akihiro Kgimoto, Hiroyuki Kasai (Univ. of Electro- Comm.) MoNA2013-2 |
In multiplex sound analysis, it is generally difficult to recognize the pitch of each sound and the instrument category ... [more] | MoNA2013-2 pp.7-12 |
| IBISML | 2012-11-07 15:30 |
Tokyo | Bunkyo School Building, Tokyo Campus, Tsukuba Univ. | Stochastic policy gradient method for a stochastic policy using a Gaussian process regression Yutaka Nakamura, Hiroshi Ishiguro (Osaka Univ.) IBISML2012-52 |
Reinforcement learning (RL) methods using Gaussian process regression (GP) for approximating the value function have bee... [more] | IBISML2012-52 pp.129-133 |
| IBISML | 2012-11-07 15:30 |
Tokyo | Bunkyo School Building, Tokyo Campus, Tsukuba Univ. | Fast Gaussian Process Regression using hash function Yuya Okadome, Yutaka Nakamura, Hiroshi Ishiguro (Osaka Univ.) IBISML2012-55 |
A Gaussian Process Regression (GPR) has ability to deal with a non-linear regression easily. However, the calculation c... [more] |
IBISML2012-55 pp.151-155 |
[Return to Top Page]