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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| PRMU, IBISML, IPSJ-CVIM | 2024-03-03 15:00 |
Hiroshima | Hiroshima Univ. Higashi-Hiroshima campus (Primary: On-site, Secondary: Online) |
Learning VQ-VAE for Image Dimensionality Reduction with Spatial Frequency Loss Naoyuki Ichimura (AIST)  PRMU2023-60 |
Vector Quantized-Variational AutoEncoders (VQ-VAEs) are a type of deep neural networks designed to learn an approximate ... [more] | PRMU2023-60 pp.53-58 |
| NC, MBE, NLP, MICT (Joint) [detail] |
2024-01-25 16:50 |
Tokushima | Naruto University of Education | Analysis of Synchrophasor Data in a Distribution Grid Using Koopman Mode Decomposition toward Dimensionality Reduction Tadahiro Yano, Yoshihiko Susuki (Kyoto Univ.) NLP2023-118 MICT2023-73 MBE2023-64 |
In this report, we study a method to reduce the dimension on highly-resolved time series data of voltage phasors measure... [more] | NLP2023-118 MICT2023-73 MBE2023-64 pp.162-165 |
| IMQ | 2023-12-22 14:00 |
Toyama | University of Toyama | [Invited Lecture]
Machine learning application for 2D/3D data analysis in material science Kentaro Kutsukake (RIKEN) IMQ2023-9 |
In materials science, data is becoming increasingly complex, high-dimension, large-scale, and numerous, consequently, hi... [more] | IMQ2023-9 pp.1-3 |
| PRMU, IPSJ-CVIM, IPSJ-DCC, IPSJ-CGVI | 2023-11-17 14:40 |
Tottori | (Primary: On-site, Secondary: Online) |
Parameter determination method for Isomap based on topological geometry Miura Suyama, Hitoshi Sakano (Shimane Univ) PRMU2023-34 |
In this study, we propose a method to determine the neighborhood parameters of Isomap, a nonlinear dimensionality reduct... [more] | PRMU2023-34 pp.103-106 |
| DE | 2023-06-16 08:50 |
Tokyo | Musashino University (Primary: On-site, Secondary: Online) |
Analysis of Impact of Interest Rate Hikes on U.S. Industry Market Capitalization
-- Time Series Data Analysis by Amplitude-based Clustering -- Saki Takabatake, Yukari Shirota (Gakushuin Univ.) DE2023-1 |
The U.S. Federal Reserve Board (FRB) has been raising the Federal Funds Rate (FF Rate), since March 2022 for price stabi... [more] | DE2023-1 pp.1-6 |
| CCS, NLP | 2023-06-09 13:55 |
Tokyo | Tokyo City Univ. | Analysis of Vocal and Ventricular Folds Data Using Machine Learning Takumi Inoue, Kota Shiozawa, Isao Tokuda (Rits Univ) NLP2023-24 CCS2023-12 |
Vocal fold vibration is a nonlinear phenomenon in the real world. In humans, vocal folds can produce complex sounds by i... [more] | NLP2023-24 CCS2023-12 pp.49-52 |
| NLP, MSS | 2023-03-15 14:20 |
Nagasaki | (Primary: On-site, Secondary: Online) |
Pareto-based dimensionality reduction of parameters for simple piecewise linear circuits Ryunosuke Numata, Toshimichi Saito (HU) MSS2022-72 NLP2022-117 |
This paper studies dimensionality reduction of parameters in switching power converters. In order to characterize the c... [more] | MSS2022-72 NLP2022-117 pp.53-57 |
| NLP | 2022-11-24 10:20 |
Shiga | (Primary: On-site, Secondary: Online) |
Reconstructing of Vocal Fold Vibration Video by Echo State Network and Dimensionality Reduction Tomu Noguchi, Kota Shiozawa, Isao Tokuda (Ritsumeikan Univ.) NLP2022-56 |
Video data provides an effective means for capturing the dynamics of experimental object. The dimensionality that actual... [more] | NLP2022-56 pp.1-4 |
| SIP | 2022-08-26 10:48 |
Okinawa | Nobumoto Ohama Memorial Hall (Ishigaki Island) (Primary: On-site, Secondary: Online) |
Instantaneous linear dimensionality reduction for array signal processing Natsuki Ueno, Nobutaka Ono (TMU) SIP2022-65 |
Linear dimensionality reduction of time-series signals observed by a sensor array is often useful in balancing the accur... [more] | SIP2022-65 pp.81-85 |
| NLP, MICT, MBE, NC (Joint) [detail] |
2022-01-23 10:55 |
Online | Online | Reward-oriented Environment Inference on Reinforcement Learning Kazuki Takahashi (Kogakuin Univ.), Tomoki Fukai (OIST), Yutaka Sakai (Tamagawa Univ.), Takashi Takekawa (Kogakuin Univ.) NC2021-42 |
Experiments on humans using the bandit problem have shown that dimensionality reduction of complex observations to a sta... [more] | NC2021-42 pp.49-54 |
| NS, RCS (Joint) |
2020-12-18 13:50 |
Online | Online | [Invited Lecture]
A Study on Higher-Order Large MIMO Detection via Concatenated Beam- and Antenna- Domain Layered BP Takumi Takahashi (Osaka Univ.), Shinsuke Ibi (Doshisha Univ.), Seiichi Sampei (Osaka Univ.) NS2020-102 RCS2020-149 |
In large multi-user multi-input multi-output systems, the computational cost and circuit scale on the base station (BS) ... [more] | NS2020-102 RCS2020-149 pp.79-84 |
| SIS, ITE-BCT | 2020-10-01 13:00 |
Online | Online | Evaluation of linear dimensionality reduction methods considering visual information protection for privacy-preserving machine learning Masaki Kitayama, Nobutaka Ono, Hitoshi Kiya (Tokyo Metro. Univ.) SIS2020-13 |
In this paper, linear dimensionality reduction methods are evaluated in terms of difficulty in estimating the visual inf... [more] | SIS2020-13 pp.17-22 |
| SIS | 2019-12-12 14:35 |
Okayama | Okayama University of Science | A Dimensionality Reduction Method with Random Sampling for Privacy-Preserving Machine Learning Ayana Kawamura, Kenta Iida, Hitoshi Kiya (Tokyo Metro. Univ.) SIS2019-26 |
In this paper, we propose a dimensionality reduction method with random sampling for privacy-preserving machine learning... [more] | SIS2019-26 pp.17-21 |
| RCS, SR, SRW (Joint) |
2019-03-06 10:30 |
Kanagawa | YRP | A Study on Layered Belief Propagation for Large MIMO Detection based on Statistical Beams Takumi Takahashi (Osaka Univ.), Antti Tolli (Univ. of Oulu), Shinsuke Ibi, Seiichi Sampei (Osaka Univ.) RCS2018-285 |
This paper proposes a novel layered belief propagation (BP) detector with a concatenated structure of two different BP l... [more] | RCS2018-285 pp.19-24 |
| NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] | 2018-06-13 10:25 |
Okinawa | Okinawa Institute of Science and Technology | Feature scaling in spectral classification of high dimensional data Momo Matsuda, Keiichi Morikuni, Akira Imakura, Tetsuya Sakurai (Univ. Tsukuba) IBISML2018-2 |
We consider the classification problem for high dimensional data. Using prior knowledge on the labels of partial samples... [more] | IBISML2018-2 pp.9-14 |
| NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] | 2018-06-13 13:25 |
Okinawa | Okinawa Institute of Science and Technology | A supervised dimensionality reduction method using linear combinations of multiple eigenvectors Akira Imakura, Momo Matsuda, Tetsuya Sakurai (Univ. Tsukuba) IBISML2018-6 |
Dimensionality reduction methods that reduce the dimension of original data to a low-dimensional subspace such as LPP an... [more] | IBISML2018-6 pp.39-45 |
| MBE, NC (Joint) |
2017-11-24 16:50 |
Miyagi | Tohoku University | NC2017-32 |
Continuous latent variable model is a category of dimension reduction methods, which estimates low dimensional latent va... [more] | NC2017-32 pp.29-34 |
| MBE, NC (Joint) |
2017-03-13 13:35 |
Tokyo | Kikai-Shinko-Kaikan Bldg. | A Generative Model of Textures Using Hierarchical Probabilistic Principal Component Analysis Aiga Suzuki, Hayaru Shouno (UEC) NC2016-83 |
Modeling of natural textures in an important task for microscopic structure of natural images. Portilla and Simon- cell... [more] |
NC2016-83 pp.115-120 |
| IE, ITS, ITE-AIT, ITE-HI, ITE-ME, ITE-MMS, ITE-CE [detail] | 2017-02-20 16:00 |
Hokkaido | Hokkaido Univ. | A note on estimating human emotion evoked by visual stimuli using fNIRS signals Kento Sugata, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.) |
This paper presents a method that estimates human emotion evoked by visual stimuli using functional near-infrared spectr... [more] | |
| IE, IMQ, MVE, CQ (Joint) [detail] |
2016-03-07 17:00 |
Okinawa | Facial expression generation based on morphable face model by impression transfer vector defined by SVM Yudai Arai, Haruna Yamaguchi, Yoshinori Inaba, Shigeru Akamatsu (Hosei Univ.) IMQ2015-47 IE2015-146 MVE2015-74 |
Facial expressions play an important role in all facets of human communication, even in human-machine communications. On... [more] | IMQ2015-47 IE2015-146 MVE2015-74 pp.107-111 |
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