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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| SIP, SP, EA, IPSJ-SLP [detail] | 2024-02-29 17:00 |
Okinawa | (Primary: On-site, Secondary: Online) |
Kernel-Induced Sampling Theorem for A Class of Mapping-Prescribed Reproducing Kernel Hilbert Spaces Akira Tanaka (Hokkaido Univ.)  EA2023-79 SIP2023-126 SP2023-61 |
A reproducing kernel is often interpreted as an inner product of two input vectors mapped into a certain space. On the c... [more] | EA2023-79 SIP2023-126 SP2023-61 pp.109-114 |
| SRW | 2022-08-22 14:40 |
Online | Online | [Invited Talk]
Towards Future-Generation Wireless Communication Technology with Multikernel Adaptive Filter
-- Partially Linear Filter for Robust Multiuser Detection -- Masahiro Yukawa (Keio Univ.) SRW2022-15 |
This review article presents a comprehensive overview of our recent developments for nonlinear multiuser detection using... [more] | SRW2022-15 pp.33-38 |
| EA, SIP, SP, IPSJ-SLP [detail] | 2022-03-01 09:20 |
Okinawa | (Primary: On-site, Secondary: Online) |
[Poster Presentation]
Direction-of-Arrival Estimation of Wideband Sound field based on Microphone Array Signals at Two Time Points Takahiro Iwami, Ken-ichi Sawai, Akira Omoto (Kyushu Univ.) EA2021-65 SIP2021-92 SP2021-50 |
We construct a band-limited function space in which the wavenumber spectrum is spherically restricted in the general dim... [more] | EA2021-65 SIP2021-92 SP2021-50 pp.9-14 |
| IBISML | 2018-11-05 15:10 |
Hokkaido | Hokkaido Citizens Activites Center (Kaderu 2.7) | [Poster Presentation]
Discovery of Governing equations in Reproducing Kernel Hilbert space Yosuke Otsubo (Nikon), Shinichi Nakajima (TUB/RIKEN) IBISML2018-65 |
It has great value in lots of scientific fields, e.g., physics, chemistry, and biology, to discover governing equations ... [more] | IBISML2018-65 pp.159-166 |
| IBISML | 2018-11-05 15:10 |
Hokkaido | Hokkaido Citizens Activites Center (Kaderu 2.7) | [Poster Presentation]
On comparison of dynamical systems via Perron-Frobenius operators on reproducing kernel Hilbert spaces Isao Ishikawa (RIKEN/Keio Univ.), Keisuke Fujii (RIKEN), Masahiro Ikeda (RIKEN/Keio Univ.), Yuka Hashimoto (Keio Univ.), Yoshinobu Kawahara (Osaka Univ/RIKEN.) IBISML2018-67 |
The development of a metric for structural data is a long-term problem in pattern recognition and machine learning. In t... [more] | IBISML2018-67 pp.175-182 |
| 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 |
|
| 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 12:40 |
Okinawa | Okinawa Industry Support Center | [Poster Presentation]
Dual-Sparsification of Kernel Regression Based on Sampling Atsushi Kojima, Toshihisa Tanaka (TUAT) EA2016-102 SIP2016-157 SP2016-97 |
When the input pattern have redundant features in regression analysis or pattern recognition, the prediction accuracy is... [more] | EA2016-102 SIP2016-157 SP2016-97 pp.115-118 |
| 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 |
| VLD, CAS, MSS, SIP | 2016-06-17 13:40 |
Aomori | Hirosaki Shiritsu Kanko-kan | Simultaneous Adaptation of Kernel Centers and Width for Kernel Adaptive Filter Tomoya Wada, Toshihisa Tanaka (TUAT) CAS2016-27 VLD2016-33 SIP2016-61 MSS2016-27 |
A kernel adaptive filter is a nonlinear adaptive filter that makes effective use of kernel methods. One of the major cha... [more] | CAS2016-27 VLD2016-33 SIP2016-61 MSS2016-27 pp.145-150 |
| CAS, SIP, MSS, VLD, SIS [detail] | 2014-07-11 10:10 |
Hokkaido | Hokkaido University | Design of Sparse Dictionary Consisting of Multiple Kernels for Kernel Adaptive Filtering Taichi Ishida, Toshihisa Tanaka (TUAT) CAS2014-35 VLD2014-44 SIP2014-56 MSS2014-35 SIS2014-35 |
A kernel adaptive filter is a nonlinear adaptive filter that makes effective use of kernel methods. Its extension is a m... [more] | CAS2014-35 VLD2014-44 SIP2014-56 MSS2014-35 SIS2014-35 pp.183-188 |
| RCS, SIP | 2014-01-23 14:40 |
Fukuoka | Kyushu Univ. | Cartesian Multikernel Adaptive Filtering Masahiro Yukawa (Keio Univ.) SIP2013-104 RCS2013-274 |
The new concept of Cartesian multikernel adaptive filtering which employs $Q$ positive definite kernels is presented. Th... [more] | SIP2013-104 RCS2013-274 pp.113-116 |
| SP, EA, SIP | 2013-05-17 11:35 |
Okayama | Multi-Kernal Adaptive Filters With Multiple Dictionaries and Regularization Taichi Ishida, Toshihisa Tanaka (Tokyo Univ. of Agriculture and Tech.) EA2013-19 SIP2013-19 SP2013-19 |
A multi-kernel adaptive filter updates filter coefficients to obtain desired data in the sum of multiple reproducing ker... [more] | EA2013-19 SIP2013-19 SP2013-19 pp.109-114 |
|
| CAS, CS, SIP | 2012-03-09 16:05 |
Niigata | The University of Niigata | A Note on Multi-Kernel Adaptive Learning Based on RKHS Projection Ryu-ichiro Ishii, Masahiro Yukawa (Niigata Univ.) CAS2011-163 SIP2011-183 CS2011-155 |
A multi-kernel adaptive learning based on RKHS projection (MKAL-RKHS) is investigated. It is first shown that the existi... [more] | CAS2011-163 SIP2011-183 CS2011-155 pp.315-320 |
| EA, SIP, SP | 2011-05-12 14:15 |
Osaka | Ritsumeikan Univ. | Multi-Kernel NLMS Algorithm with Coherence Criterion and Its Application to Online Prediction of Time Series Data Masahiro Yukawa (Niigata Univ.) EA2011-14 SIP2011-14 SP2011-14 |
In this paper, we propose a nonlinear adaptive filtering algorithm using multiple kernels. The proposed algorithm is a g... [more] | EA2011-14 SIP2011-14 SP2011-14 pp.79-82 |
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