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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 43  /  [Next]  
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
(To be available after the conference date) [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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