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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| NLP, MSS | 2023-03-15 15:55 |
Nagasaki | (Primary: On-site, Secondary: Online) |
Curve Fitting Analysis for Blood Flow of Gastric Tube Daisuke Katsuragi, Yasunori Kurahashi (Hyogo Medical Univ.)  MSS2022-76 NLP2022-121 |
After the esophagectomy, the success or failure of the gullet rebuilding greatly depends on the blood flow of gastric ... [more] |
MSS2022-76 NLP2022-121 pp.71-74 |
| EST | 2023-01-26 14:50 |
Okinawa | (Primary: On-site, Secondary: Online) |
Design of thin dielectric lens for millimeter-wave antenna using high dielectric constant materials Keiichi Itoh, Junya Satoh, Shun Togase, Masaki Tanaka (NIT, Akita College), Hajime Igarashi (Hokkaido Univ.) EST2022-84 |
This paper describes a design method for thin dielectric lenses for millimeter-wave antennas using high dielectric const... [more] | EST2022-84 pp.53-57 |
| QIT (2nd) |
2022-12-08 14:00 |
Kanagawa | Keio Univ. (Primary: On-site, Secondary: Online) |
[Poster Presentation]
Two-photon phase singularity manifested by propagational distance control of photon pair generated by higher-order LG pump beam Takumi Jinushi, Hirokazu Kobayashi (KUT) |
We report our finding that a phase singularity in two-photon wave function is manifested at the center of the optical ax... [more] | |
| 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 |
| NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] | 2022-06-27 17:50 |
Okinawa | (Primary: On-site, Secondary: Online) |
Comparison of Variational Bayes and Gibbs Sampling for Normal Inverse Gaussian Mixture Models Takashi Takekawa (Kogakuin Univ.) NC2022-9 IBISML2022-9 |
Mixture models for multivariate normal distributions (GMM) are widely used for data clustering. To compensate for the s... [more] | NC2022-9 IBISML2022-9 pp.76-79 |
| HCS, HIP, HI-SIGCE [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 |
| IE | 2022-01-24 12:40 |
Tokyo | National Institute of Informatics (Primary: On-site, Secondary: Online) |
Acceleration of Bilateral Filter by Approximating Gaussian Weight Calculation Fumiya Kojima (NITech), Yoshihiro Maeda (TUS), Norishige Fukushima (NITech) IE2021-33 |
Bilateral filter is a typical edge-preserving smoothing filter that uses a Gaussian distribution.The Gaussian distributi... [more] | IE2021-33 pp.33-38 |
| AP, RCS (Joint) |
2021-11-10 16:20 |
Nagasaki | NBC-Bekkan (Nagasaki) (Primary: On-site, Secondary: Online) |
Maxmin Rate Optimization for MISO-NOMA Systems with Transmit Beamforming and Antenna Selection Based on Improper Gaussian Signaling Hao-Tse Chiu, Fumiaki Maehara (Waseda Univ.) RCS2021-154 |
In this report, we consider the joint antenna selection (AS) and beamforming (BF) vector design problem for a downlink t... [more] | RCS2021-154 pp.58-62 |
| MIKA (3rd) |
2021-10-29 10:30 |
Okinawa | (Primary: On-site, Secondary: Online) |
[Poster Presentation]
Comments on the Closed Form Expression of Average Block Error Rate in Finite Block-Length Transmission over Fading Channels Masaya Kambara, Tomotaka Kimura, Jun Cheng (Doshisha Univ.) |
It is well-known that a closed form expression is derived to give an average block error rate of finite-blocklength tran... [more] | |
| IT | 2021-07-09 14:30 |
Online | Online | Construction of Dimension Reduction Matrix for Signal Recovery of Multivariate Gaussian Vectors Kento Yokoyama, Tadashi Wadayama, Satoshi Takabe (NIT) IT2021-26 |
In compressed sensing, we discuss the problem of estimating the sparse original signal $¥bm{x} ¥in ¥mathbb{R}^n$ from th... [more] | IT2021-26 pp.63-68 |
| SIS | 2021-03-05 10:00 |
Online | Online | Prediction of Network Traffic through Gaussian Process Yitu Wang, Takayuki Nakachi (NTT) SIS2020-54 |
With accurate network traffic prediction, future communication networks can realize self-management and enjoy intelligen... [more] | SIS2020-54 pp.103-108 |
| IBISML | 2020-10-21 10:25 |
Online | Online | IBISML2020-19 |
Due to the decreasing birthrate and labor force, expectations are rising for the automatic operation of various robots a... [more] | IBISML2020-19 p.36 |
| SP, EA, SIP | 2020-03-02 10:10 |
Okinawa | Okinawa Industry Support Center (Cancelled but technical report was issued) |
Multichannel NMF with Joint-Diagonalizable Constraint Based on Generalized Gaussian Distribution for Blind Source Separation Keigo Kamo, Yuki Kubo, Norihiro Takamune (UTokyo), Daichi Kitamura (NIT Kagawa), Hiroshi Saruwatari (UTokyo), Yu Takahashi, Kazunobu Kondo (Yamaha) EA2019-103 SIP2019-105 SP2019-52 |
Multichannel nonnegative matrix factorization (MNMF) is a blind source separation technique, which employs the full-rank... [more] | EA2019-103 SIP2019-105 SP2019-52 pp.13-19 |
| EA | 2019-12-13 13:25 |
Fukuoka | Kyushu Inst. Tech. | Rank-constrained spatial covariance matrix estimation based on multivariate complex generalized Gaussian distribution and its acceleration for blind speech extraction Yuki Kubo, Norihiro Takamune (UTokyo), Daichi Kitamura (NIT, Kagawa), Hiroshi Saruwatari (UTokyo) EA2019-78 |
In this paper, we generalize a generative model in rank-constrained spatial covariance matrix estimation that separates ... [more] | EA2019-78 pp.85-92 |
| NC, IBISML, IPSJ-MPS, IPSJ-BIO [detail] | 2019-06-17 15:50 |
Okinawa | Okinawa Institute of Science and Technology | A Comparison of Surrogate Models in Bayesian Optimization Sho Shimoyama (Meiji Univ.), Masahiro Nomura (CA) IBISML2019-7 |
Bayesian optimization can efficiently select the next search point by using a surrogate model that estimates an objectiv... [more] | IBISML2019-7 pp.43-50 |
| SANE | 2018-11-09 10:30 |
Overseas | China (Xuchang) | Investigation of the effect of bispectrum on scattering from non-Gaussian sea surface Dengfeng Xie (RADI/CAS/UCAS/CHN), Kun-Shan Chen (RADI/CAS/CHN) SANE2018-85 |
The upwind-downwind asymmetry in normalized radar backscattering cross section (NRBCS) from ocean surface is well-known;... [more] | SANE2018-85 pp.147-152 |
| IBISML | 2018-11-05 15:10 |
Hokkaido | Hokkaido Citizens Activites Center (Kaderu 2.7) | [Poster Presentation]
Active learning for identifying local minimum points based on the derivative of Gaussian process Yu Inatsu (RIKEN), Daisuke Sugita (NITech), Kazuaki Toyoura (Kyoto Univ.), Ichiro Takeuchi (NITech/RIKEN/NIMS) IBISML2018-94 |
In many fields such as materials science, knowing local minimum points of unknown functions is important for understand... [more] | IBISML2018-94 pp.373-380 |
| 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 |
|
| PRMU, IBISML, IPSJ-CVIM [detail] | 2017-09-15 10:30 |
Tokyo | Experimental Analysis of Variational Bayesian Method in Model Selection of Gaussian Mixture Model by Singular Bayesian Information Criterion Naoki Hayashi (Tokyo Tech), Fumito Nakamura (Bosch) PRMU2017-41 IBISML2017-13 |
A Gaussian mixture model (GMM) is a statistical model used in various fields such a pattern recognition, thus, it is imp... [more] | PRMU2017-41 IBISML2017-13 pp.19-26 |
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