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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| IT | 2022-07-22 13:50 |
Okayama | Okayama University of Science (Primary: On-site, Secondary: Online) |
An Efficient Algorithm for Optimal Decision on Piecewise Linear Regression Model by Bayes Decision Theory Noboru Namegaya, Koshi Shimada, Toshiyasu Matsushima (Waseda Univ.)  IT2022-25 |
In this study, we propose a Beyes-optimal prediction method on a piecewise linear regression model by Bayes decision the... [more] | IT2022-25 pp.51-55 |
| IBISML | 2021-03-04 14:40 |
Online | Online | IBISML2020-59 |
In the machine learning tasks where the training data is scarce, domain adaptation (DA) is a promising methodology that ... [more] | IBISML2020-59 p.78 |
| SIP, EA, SP, MI (Joint) [detail] |
2018-03-19 14:45 |
Okinawa | Optimization of Gaussian Kernel Parameters for Kernel Logistic Regression Kosuke Fukumori, Tomoya Wada, Toshihisa Tanaka (TUAT) EA2017-135 SIP2017-144 SP2017-118 |
The kernel logistic regression is a nonlinear classification model that effectively uses kernel methods, which are one o... [more] | EA2017-135 SIP2017-144 SP2017-118 pp.185-190 |
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| SIP, CAS, MSS, VLD | 2017-06-20 11:00 |
Niigata | Niigata University, Ikarashi Campus | On Contributions of Principal Eigenfunctions of Covariance Operator of Kernel Feature Vectors to Relevant Information in Nonlinear Regression Masahiro Yukawa (Keio Univ.), Klaus-Robert Muller (TU BerlinTechnical U) CAS2017-16 VLD2017-19 SIP2017-40 MSS2017-16 |
We study, through simple non-asymptotic arguments, the contributions of eigenfunctions of the covariance operator of ker... [more] | CAS2017-16 VLD2017-19 SIP2017-40 MSS2017-16 pp.81-85 |
| SP, SIP, EA | 2017-03-01 15:55 |
Okinawa | Okinawa Industry Support Center | [Invited Talk]
Multikernel Adaptive Filtering: Signal Processing and Machine Learning Masahiro Yukawa (Keio Univ.) EA2016-113 SIP2016-168 SP2016-108 |
We present the multikernel adaptive filtering and introduce its recent advances. Multikernel adaptive filtering is a rec... [more] | EA2016-113 SIP2016-168 SP2016-108 pp.177-182 |
| RCS, SR, SRW (Joint) |
2015-03-04 09:00 |
Tokyo | Tokyo Institute of Technology | A Study on Estimation of Amplifier Nonlinearity for Adjacent Channel Interference Cancellation in Millimeter Wave Communication Systems Noboru Osawa, Shinsuke Ibi, Kei Sakaguchi, Seiichi Sampei (Osaka Univ.) RCS2014-308 |
This paper proposes an estimation method of amplifier nonlinearity for adjacent channel interference (ACI) cancellation ... [more] | RCS2014-308 pp.41-46 |
| IBISML | 2014-11-18 15:00 |
Aichi | Nagoya Univ. | [Poster Presentation]
Nonlinear Regression Using Deep Learning Wataru Uchiyama, Toshiyuki Tanaka (Kyoto Univ.) IBISML2014-81 |
In recent years, deep learning has been attracting a great deal of researchers' attention with its performance reported ... [more] | IBISML2014-81 pp.345-349 |
| KBSE | 2013-01-29 12:00 |
Tokyo | Kikai-Shinko-Kaikan Bldg | Multi-layered GMDH-type neural network algorithm using Prediction Sum of Squares (PSS) criterion and Its application to nonlinear system identification Tadashi Kondo, Junji Ueno, Shoichiro Takao (Tokushima Univ.) KBSE2012-64 |
In this study, a revised Group Method of Data Handling (GMDH)-type neural network using Prediction Sum of Squares (PSS) ... [more] | KBSE2012-64 pp.35-40 |
| SIP, RCS | 2011-01-20 14:55 |
Kagoshima | A Numerical Study on Online Regression with Multiple Kernels You Nakajima, Masahiro Yukawa (Niigata Univ.) SIP2010-91 RCS2010-221 |
In this paper, we investigate by simulations the potential performance of an online learning technique with multiple ker... [more] | SIP2010-91 RCS2010-221 pp.133-136 |
|
| IBISML, PRMU, IPSJ-CVIM [detail] | 2010-09-06 13:40 |
Fukuoka | Fukuoka Univ. | [Fellow Memorial Lecture]
- Takio Kurita (Hiroshima Univ.) PRMU2010-84 IBISML2010-56 |
Linear Discriminant Analysis (LDA) is one of the well known methods to extract good features for classification. Otsu de... [more] | PRMU2010-84 IBISML2010-56 pp.209-214 |
| SP, NLC | 2009-12-21 10:10 |
Tokyo | Univ. of Tokyo | Speaker Adaptation Using Nonlinear Spectral Transformation For Speech Recognition. Toyohiro Hayashi, Yoshihiko Nankaku, Akinobu Lee, Keiichi Tokuda (Nagoya Inst. of Tech.) NLC2009-12 SP2009-76 |
This paper proposes a speaker adaptation technique using nonlinear spectral transform based on GMMs. One of the most po... [more] |
NLC2009-12 SP2009-76 pp.1-6 |
| NLP | 2009-11-13 10:45 |
Kagoshima | Partialization Analysis for Nonlinear Connections of Second Order Kaori Kuroda, Tohru Ikeguchi (Saitama Univ.) NLP2009-102 |
Real systems often produce very complicated behavior due to complex interactions between elements in the system. In orde... [more] | NLP2009-102 pp.115-120 |
|
| CQ | 2009-09-11 10:30 |
Gifu | Takayama Culture Center | Estimation of QoE with Nonlinear Multiple Regression Analysis in Interactive Audiovisual IP Communications Toshiro Nunome, Shuji Tasaka, Yuta Osawa (Nagoya Inst. of Tech.) CQ2009-36 |
This report studies estimation methods of QoE (Quality of Experience) of interactive audiovisual applications in bandwid... [more] | CQ2009-36 pp.59-64 |
| MBE | 2009-05-22 11:10 |
Toyama | Toyama Univ. | An Attempt of a Novel Calibration Method for Pulse Oximetry Using Support Vector Machines Non-Linear Regression Hirotaka Nomoto, Mitsuhiro Ogawa (Kanawaza Univ), Yasuhiro Yamakoshi (yu.sys Corp.), Masamichi Nogawa, Takehiro Yamakoshi, Kosuke Motoi, Shinobu Tanaka, Ken-ichi Yamakoshi (Kanawaza Univ) MBE2009-2 |
A new calibration method using a non linear multivariate regression method, support vector machines regression (SVMsR) o... [more] | MBE2009-2 pp.5-8 |
| PRMU, NLC | 2005-02-24 10:30 |
Tokyo | MDL-based nonlinear regression tree Yoshimi Uezu, Takayuki Nakamura, Toshikazu Wada (Wakayama Univ.) |
In the previous work, we proposed the ''\ PaLM-Tree '' which is a kind of linear regression tree. It improves some drawb... [more] | NLC2004-99 PRMU2004-181 pp.13-18 |
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| MBE | 2005-01-29 14:30 |
Fukuoka | Kyushu Inst. of Tech. | Examination of EEG analysis by mutual information Takamasa Yoshida (Kagoshima Univ.), Keita Tanaka (Denki Univ.), Masayoshi Naito (Tokyo Woman's Christian Univ.), Kazutomo Yunokuchi (Kagoshima Univ.) |
Detection of nonlinearity in EEG signals by mutual information and linear regression model was performed. Firstly, it wa... [more] | MBE2004-86 pp.53-56 |
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