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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| IBISML | 2023-12-20 14:55 |
Tokyo | National Institute of Informatics (Primary: On-site, Secondary: Online) |
Anomaly Detection by One-class Convolution Extreme Learning Machine Using Multiple Kernel Yuta Okami, Takuya Kitamura (NIT, Toyama College)  IBISML2023-31 |
In this paper, we propose a one-class convolutional extreme learning machine using multiple kernel. In this method, for ... [more] | IBISML2023-31 pp.7-12 |
| EA, SIP, SP | 2019-03-14 13:30 |
Nagasaki | i+Land nagasaki (Nagasaki-shi) | [Poster Presentation]
Snore sound identification using noise suppression and multi-class classification under real environments Keisuke Nishijima, Ken'ichi Furuya (Oita Univ.) EA2018-106 SIP2018-112 SP2018-68 |
In the conventional snore sound identification method, there is an issue that performance deteriorates when identifying ... [more] | EA2018-106 SIP2018-112 SP2018-68 pp.43-48 |
| 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 |
| PRMU, FM | 2011-12-16 10:00 |
Shizuoka | Hamamatsu Campus, Shizuoka Univ. | Food region detection using Deformable Part Model Yuji Matsuda, Keiji Yanai (UEC) PRMU2011-133 |
(To be available after the conference date) [more] | PRMU2011-133 pp.47-51 |
| IBISML | 2011-11-09 15:45 |
Nara | Nara Womens Univ. | On Fast Convergence Rate of Non-Sparse Multiple Kernel Learning and Optimal Regularization Taiji Suzuki (Tokyo University) IBISML2011-64 |
In this paper, we give a new generalization error bound of Multiple Kernel Learning (MKL) for a general class of regular... [more] | IBISML2011-64 pp.147-154 |
| IBISML | 2011-11-10 15:45 |
Nara | Nara Womens Univ. | Semi-supervised domain adaptation with multiple kernel learning Hiroyuki Okada, Kuniaki Uehara (Kobe Univ.) IBISML2011-79 |
We are interested in the problem of domain adaptation，a branch of transfer learning. Traditional, unsupervised, domain... [more] |
IBISML2011-79 pp.251-256 |
| PRMU, IBISML, IPSJ-CVIM [detail] | 2011-09-06 14:50 |
Hokkaido | A Method for Multiple Instance Learning Using Sparse Kernel Machines Kazuhisa Nagashima, Masato Inoue (Waseda Univ.) PRMU2011-77 IBISML2011-36 |
Multiple Instance Learning problem (MIL) is roughly one of the classification problems. In generally classification pr... [more] |
PRMU2011-77 IBISML2011-36 pp.159-163 |
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| IBISML | 2011-03-29 16:30 |
Osaka | Nakanoshima Center, Osaka Univ. | Fast Convergence Rate of Multiple Kernel Learning with Elastic-net Regularization Taiji Suzuki, Ryota Tomioka (Univ. of Tokyo), Masashi Sugiyama (Tokyo Inst. of Tech.) IBISML2010-126 |
We investigate the learning rate of multiple kernel leaning (MKL) with elastic-net regularization, which consists of a... [more] |
IBISML2010-126 pp.153-160 |
| SP | 2011-01-28 10:15 |
Kyoto | NICT | Feature Selection for Single-Channel Sound Source Localization Using the Acoustic Transfer Function Ryoichi Takashima, Tetsuya Takiguchi, Yasuo Ariki (Kobe Univ.) SP2010-111 |
This paper presents a sound source (talker) localization method using only a single microphone. In our previous work, w... [more] | SP2010-111 pp.49-54 |
| IBISML | 2010-11-05 15:30 |
Tokyo | IIS, Univ. of Tokyo | [Poster Presentation]
Regularization Strategies and Empirical Bayesian Learning for MKL Ryota Tomioka, Taiji Suzuki (Univ. of Tokyo) IBISML2010-100 |
Multiple kernel learning (MKL) has received considerable attention recently. In this paper, we show how different MKL al... [more] | IBISML2010-100 pp.303-310 |
| IBISML, PRMU, IPSJ-CVIM [detail] | 2010-09-05 09:30 |
Fukuoka | Fukuoka Univ. | Multiple Kernel Learning for Generic Object Recognition Using SIFT Gaussian Mixture Models Nakamasa Inoue, Yusuke Kamishima, Koichi Shinoda, Sadaoki Furui (Tokyo Tech) PRMU2010-58 IBISML2010-30 |
We propose a statistical framework for generic object recognition using SIFT Gaussian mixture models (GMMs) and multiple... [more] | PRMU2010-58 IBISML2010-30 pp.7-12 |
| PRMU | 2009-08-31 14:40 |
Miyagi | Tohoku Univ. | [Special Talk]
Optimization algorithms for sparse regularization and multiple kernel learning and their applications to CV/PR Ryota Tomioka, Taiji Suzuki, Masashi Sugiyama (Univ. of Tokyo.) PRMU2009-63 |
Convex sparse regularization is increasingly becoming recognized as a principled framework for selecting informative fe... [more] |
PRMU2009-63 pp.43-48 |
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