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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| IE, MVE, CQ, IMQ (Joint) [detail] |
2024-03-14 10:30 |
Okinawa | Okinawa Sangyo Shien Center (Primary: On-site, Secondary: Online) |
Informative Path Planning in Dynamic Environments Using Spatio-Temporal Gaussian Process Regression Gao Tian, Techasarntikul Nattaon, Ohsita Yuichi, Shimonishi Hideyuki (Osaka Univ.)  CQ2023-80 |
With the rapid advancement of automation technology, the role of autonomous robots in environmental monitoring and explo... [more] | CQ2023-80 pp.56-61 |
| 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 |
| RISING (3rd) |
2023-10-31 09:45 |
Hokkaido | Kaderu 2・7 (Sapporo) | [Poster Presentation]
LOS/NLOS estimation using Gaussian process regression in indoor millimeter-wave beamforming Takumi Bushi, Kenji Ohira, Hideyuki Shimonishi (Osaka Univ.) |
Various automations using mobile devices like robots are advancing, and with the collection of large data from cameras,... [more] |
|
| 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 |
| 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 |
| HWS, VLD | 2023-03-02 13:25 |
Okinawa | (Primary: On-site, Secondary: Online) |
[Memorial Lecture]
Wafer-Level Characteristic Variation Modeling Considering Systematic Discontinuous Effects Takuma Nagao (NAIST), Tomoki Nakamura, Masuo Kajiyama, Makoto Eiki (Sony Semiconductor Manufacturing), Michiko Inoue (NAIST), Michihiro Shintani (Kyoto Institute of Technology) VLD2022-91 HWS2022-62 |
Statistical wafer-level variation modeling is an attractive method for reducing the measurement cost in large-scale inte... [more] | VLD2022-91 HWS2022-62 p.109 |
| 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 |
| HCS, HIP, HI-SIGCOASTER [detail] | 2022-05-15 15:35 |
Okinawa | Okinawa Industry Support Center (Primary: On-site, Secondary: Online) |
Examination of morphological traits of children's faces related to perceptions of cuteness using Gaussian process ordinal regression Teppei Teraji, Keito Shiroshita, Masashi Komori (OECU), Hiroshi Nittono (Osaka Univ.) HCS2022-17 HIP2022-17 |
Konrad Lorenz, an ethologist, proposed that certain physical elements are perceived as cute and induce caretaking behavi... [more] | HCS2022-17 HIP2022-17 pp.81-85 |
| 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 |
| EMM | 2022-03-08 11:50 |
Online | (Primary: Online, Secondary: On-site) (Primary: Online, Secondary: On-site) |
RUT Computation of Gaussian Process Regression for Encrypting Input and Output Signals Takayuki Nakachi (Univ. of the Ryukyus), Yitu Wang (NTT) EMM2021-115 |
n this paper, we propose Gaussian Process Regression (GPR) for encrypted data generated based on random unitary transfor... [more] | EMM2021-115 pp.124-129 |
| 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 |
| SIS, IPSJ-AVM | 2021-06-24 13:45 |
Online | Online | Privacy-Preserving Secure Computation of Gaussian Process Regression
-- Find patterns and rules from encrypted data -- Takayuki Nakachi (Univ. of the Ryukyus), Yitu Wang (NTT) SIS2021-8 |
In this paper, we propose Gaussian Process Regression (GPR) for encrypted data generated based on random unitary transfo... [more] | SIS2021-8 pp.43-48 |
| 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 |
| NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] | 2018-06-13 10:00 |
Okinawa | Okinawa Institute of Science and Technology | Active Level Set Estimation with Multi-fidelity Evaluations Shion Takeno (Nitech), Hitoshi Fukuoka (Nagoya Univ.), Yuhki Tsukada (Nagoya Univ./JST), Toshiyuki Koyama (Nagoya Univ.), Motoki Shiga (Gifu Univ./JST/RIKEN), Ichiro Takeuchi (NITech/NIMS/RIKEN), Masayuki Karasuyama (NITech/NIMS/JST) IBISML2018-1 |
Level set estimation is a problem to identify a level set of an unknown function, which is defined by whether the functi... [more] | IBISML2018-1 pp.1-8 |
| SIP, EA, SP, MI (Joint) [detail] |
2018-03-19 10:50 |
Okinawa | On the Use of Deep Gaussian Processes for GPR-based Speech Synthesis Tomoki Koriyama, Takao Kobayashi (Tokyo Inst. of Tech.) EA2017-106 SIP2017-115 SP2017-89 |
This paper proposes a speech synthesis framework based on deep Gaussian processes (DGPs). DGP is a Bayesian deep learn... [more] |
EA2017-106 SIP2017-115 SP2017-89 pp.27-32 |
|
| 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 |
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