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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 19 of 19  /   
Committee Date Time Place Paper Title / Authors Abstract Paper #
PRMU, IPSJ-CVIM 2020-03-17
16:50
Kyoto
(Cancelled but technical report was issued)
Experimental Evaluation for Bayes Error Estimation Capability of Large Geometric Margin Minimum Classification Error Training
Ikuhiro Nishiyama (Doshisha Univ.), Hideyuki Watanabe (ATR), Shigeru Katagiri, Miho Ohsaki (Doshisha Univ.) PRMU2019-99
Previous studies suggested that the Large Geometric Margin-Minimum Classification Error (LGM-MCE) training method had th... [more] PRMU2019-99
pp.231-236
PRMU, IPSJ-CVIM 2020-03-17
17:05
Kyoto
(Cancelled but technical report was issued)
Experimental Evaluation on Bayes Error Estimation Capability of Kernel Minimum Classification Error Training
Koji Yamada (Doshisha Univ.), Hideyuki Watanabe (ATR), Shigeru Katagiri, Miho Ohsaki (Doshisha Univ.) PRMU2019-100
A pattern classifier incorporating kernel mapping, which is trained by the Kernel Minimum Classification Error (KMCE) tr... [more] PRMU2019-100
pp.237-242
PRMU 2018-12-14
15:50
Miyagi   Bayes Boundary Estimation Capability Assessment for Large Geometric Margin Minimum Classification Error Training
Ikuhiro Nishiyama (Doshisha Univ.), Hideyuki Watanabe (ATR), Shigeru Katagiri, Miho Osaki (Doshisha Univ.) PRMU2018-92
The recent, Large Geometric Margin Minimum Classification Error training has, based on the smoothness of its smooth clas... [more] PRMU2018-92
pp.91-96
PRMU, CNR 2017-02-18
11:20
Hokkaido   Small-sized Kernel Classifier By Support Vector Retraining Based on Minimum Classification Error Criterion
Ryoma Tani (Doshisha Univ.), Hideyuki Watanabe (ATR), Shigeru Katagiri, Miho Osaki (Doshisha Univ.) PRMU2016-159 CNR2016-26
Different from the Multi-class Support Vector Machine (MSVM) that fixes Support Vectors (SVs) to training samples, the K... [more] PRMU2016-159 CNR2016-26
pp.41-46
PRMU 2015-12-21
09:30
Nagano   Evaluation of Automatic Prototype-Model Size Optimization in Large Geometric Margin Minimum Classification Error Training
Masahiro Ogino (Doshisha Univ.), Hideyuki Watanabe (NICT), Shigeru Katagiri, Miho Osaki (Doshisha Univ.), Xugang Lu, Hisashi Kawai (NICT) PRMU2015-100
To develop a method for nding an appropriate class model size, which leads to accurate classi cation over unseen patter... [more] PRMU2015-100
pp.1-6
PRMU, IPSJ-CVIM, MVE [detail] 2015-01-23
09:50
Nara   Analysis of Minimum Classification Error Training using Bit-String-Based Genetic Algorithms
Hiroto Togoe (Doshisha Univ.), Hideyuki Watanabe (NICT), Shigeru Katagiri (Doshisha Univ.), Xugang Lu, Chiori Hori (NICT), Miho Ohsaki (Doshisha Univ.) PRMU2014-100 MVE2014-62
Minimum Classification Error (MCE) training using gradient-descent-based loss minimization does not guarantee a global m... [more] PRMU2014-100 MVE2014-62
pp.171-176
PRMU, IPSJ-CVIM, MVE [detail] 2015-01-23
10:15
Nara   Relation between Data Grouping and Robustness to Unseen Data in Large Geometric Margin Minimum Classification Error Training
Hiroyuki Shiraishi (Doshisha Univ), Hideyuki Watanabe (NICT), Shigeru Katagiri (Doshisha Univ), Xugang Lu, Chiori Hori (NICT), Miho Ohsaki (Doshisha Univ) PRMU2014-101 MVE2014-63
To develop a pattern classifier that is robust to unseen pattern samples, classifier parameters have been conventionally... [more] PRMU2014-101 MVE2014-63
pp.177-182
PRMU, IPSJ-CVIM, MVE [detail] 2014-01-23
09:30
Osaka   Minimum Classification Error Training with Automatic Determination of Loss Smoothness Common to All Classes
Kensuke Ota (Doshisha Univ.), Hideyuki Watanabe (NICT), Shigeru Katagiri, Miho Ohsaki (Doshisha Univ.), Shigeki Matsuda, Chiori Hori (NICT) PRMU2013-91 MVE2013-32
The smoothness of the smooth classification error count loss used in the Minimum Classification Error (MCE) training has... [more] PRMU2013-91 MVE2013-32
pp.1-6
PRMU, IPSJ-CVIM, MVE [detail] 2014-01-23
10:00
Osaka   Minimum Classification Error Training with Automatic Control of Loss Smoothness
Hideaki Tanaka (Doshisha Univ.), Hideyuki Watanabe (NICT), Shigeru Katagiri, Miho Ohsaki (Doshisha Univ.), Shigeki Matsuda, Chiori Hori (NICT) PRMU2013-92 MVE2013-33
The Minimum Classification Error (MCE) training has been successfully applied to various types of classifiers. However, ... [more] PRMU2013-92 MVE2013-33
pp.7-12
PRMU, IPSJ-CVIM, MVE [detail] 2014-01-23
10:30
Osaka   Multi-Class Support Vector Machine based on Minimum Classification Error Criterion
Hisashi Uehara (Doshisha Univ.), Hideyuki Watanabe (NICT), Shigeru Katagiri, Miho Ohsaki (Doshisha Univ.), Shigeki Matsuda, Chiori Hori (NICT) PRMU2013-93 MVE2013-34
Gradient-descent-based optimization methods used in Minimum Classification Error (MCE) training are not necessarily easi... [more] PRMU2013-93 MVE2013-34
pp.13-18
PRMU, IPSJ-CVIM, MVE [detail] 2014-01-23
11:00
Osaka   Large Geometric Margin Minimum Classification Error Training with Automatic Optimization Of The Number of Prototypes
Yuji Takayama (Doshisha Univ.), Hideyuki Watanabe (NICT), Shigeru Katagiri, Miho Ohsaki (Doshisha Univ.), Shigeki Matsuda, Chiori Hori (NICT) PRMU2013-94 MVE2013-35
Large Geometric Margin Minimum Classification Error (LGM-MCE) training, which adopts geometric-margin-based misclassific... [more] PRMU2013-94 MVE2013-35
pp.19-24
ITS, IE, ITE-AIT, ITE-HI, ITE-ME [detail] 2012-02-20
15:40
Hokkaido Hokkaido Univ. Experimental Evaluation of Image Object Tracking Method using Particle Filter and Minimum Classification Error Training
Jyun'ichi Nakamura, Shigeru Katagiri, Miho Ohsaki (Doshisha Univ) ITS2011-36 IE2011-112
To increase the accuracy of image object tracking, a discriminative tracking method was proposed that combined the parti... [more] ITS2011-36 IE2011-112
pp.79-84
PRMU 2011-03-11
09:30
Ibaraki   Application of Automatic Loss Smoothness Control to Large Geometric Margin Minimum Classification Error Training
Tsukasa Ohashi (Doshisha Univ.), Hideyuki Watanabe (NICT), Jun'ichi Tokuno, Shigeru Katagiri, Miho Ohsaki (Doshisha Univ.) PRMU2010-270
A method that automatically controls the smoothness of a smoothed classification error count loss using Parzen estimatio... [more] PRMU2010-270
pp.195-200
PRMU, FM 2010-12-10
15:20
Yamaguchi   Comparison between Minimum Classification Error Training and Support Vector Machine in Prototype-based Classifier Design
Mamoru Adachi (Doshisha Univ.), Hideyuki Watanabe (NICT), Shigeru Katagiri, Miho Ohsaki (Doshisha Univ.) PRMU2010-146
In this paper, we experimentally compared the size of trained classifier class models (prototypes) between Support Vecto... [more] PRMU2010-146
pp.107-112
IBISML, PRMU, IPSJ-CVIM [detail] 2010-09-06
10:40
Fukuoka Fukuoka Univ. Minimum Classification Error Training with Automatic Control of Loss Smoothness
Junichi Tokuno (Doshisha Univ.), Hideyuki Watanabe (NICT), Shigeru Katagiri, Miho Ohsaki (Doshisha Univ.) PRMU2010-80 IBISML2010-52
The smoothness embedded in the Minimum Classification Error formalization has an effect of increasing virtual training s... [more] PRMU2010-80 IBISML2010-52
pp.179-184
PRMU 2009-11-27
13:00
Ishikawa Ishikawa Industrial Promotion Center Finger Recognition using Particle Filter and Minimum Classification Error Training
Kosuke Kiyota, Shigeru Katagiri (Doshisha Univ.), Hideyuki Watanabe (NICT), Miho Ohsaki (Doshisha Univ.) PRMU2009-125
This paper proposes a new method for recognizing a finger used as a pointer to operate a remote collaboration assistant ... [more] PRMU2009-125
pp.235-240
PRMU 2009-08-31
10:00
Miyagi Tohoku Univ. Geometric Margin for a General Class of Discriminant Functions and Its Control for Minimum Error Classification
Hideyuki Watanabe (NICT), Shigeru Katagiri, Kouta Yamada (Doshisha Univ.), Erik McDermott, Atsushi Nakamura, Shinji Watanabe (NTT Corp.), Miho Ohsaki (Doshisha Univ.) PRMU2009-60
The recent dramatic growth of computation power has resulted in increased interests in discriminative training (DT) meth... [more] PRMU2009-60
pp.1-6
PRMU 2009-09-01
09:00
Miyagi Tohoku Univ. Implementation and Experimental Evaluation of Ensemble Minimum Classification Error Training
Shin'ichi Taniguchi (Doshisha University), Hideyuki Watanabe (NICT), Shigeru Katagiri, Kohta Yamada (Doshisha University), Atsushi Nakamura, Erik McDermott, Shinji Watanabe (NTT), Naho Nishijima, Miho Ohsaki (Doshisha Univ.) PRMU2009-67
Recently, we developed a noble Ensemble-based Minimum Classification Error training method (EMCE) by combining the advan... [more] PRMU2009-67
pp.103-108
SP 2009-07-17
13:50
Fukushima   Geometric Margin Control for Minimum Error Classification
Kouta Yamada, Shigeru Katagiri (Doshisha Univ.), Erik McDermott (NTT), Hideyuki Watanabe (NICT), Atsushi Nakamura, Shinji Watanabe (NTT), Miho Ohsaki (Doshisha Univ.) SP2009-43
The recent dramatic growth of computation power and data availability has increased research interests in discriminative... [more] SP2009-43
pp.13-18
 Results 1 - 19 of 19  /   
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