Shigeo Abe

Takashi Nagatani, Shigeo Abe: Feature Selection by Block Addition and Block Deletion. ANNPR 2012: 48-59

Shigeo Abe: Training Mahalanobis Kernels by Linear Programming. ICANN (2) 2012: 339-346

Shigeo Abe: Fast Support Vector Training by Newton's Method. ICANN (2) 2011: 143-150

Takuya Kitamura, Shigeo Abe, Yusuke Tanaka: Multiple Nonlinear Subspace Methods Using Subspace-based Support Vector Machines. ICMLA (1) 2011: 358-363

Tao Ban, Changshui Zhang, Shigeo Abe, Takeshi Takahashi, Youki Kadobayashi: Mining interlacing manifolds in high dimensional spaces. SAC 2011: 942-949

Takashi Nagatani, Seiichi Ozawa, Shigeo Abe: Fast Variable Selection by Block Addition and Block Deletion. JILSA 2(4): 200-211 (2010)

Tsuneyoshi Ishii, Shigeo Abe: Evaluation of Feature Selection by Multiclass Kernel Discriminant Analysis. ANNPR 2010: 13-24

Shigeo Abe: Active set training of support vector regressors. ESANN 2010

Shigeo Abe, Ryousuke Yabuwaki: Convergence Improvement of Active Set Training for Support Vector Regressors. ICANN (2) 2010: 1-10

Yasuyuki Tajiri, Ryousuke Yabuwaki, Takuya Kitamura, Shigeo Abe: Feature Extraction Using Support Vector Machines. ICONIP (2) 2010: 108-115

Takuya Kitamura, Syogo Takeuchi, Shigeo Abe: Feature selection and fast training of subspace based support vector machines. IJCNN 2010: 1-6

Ryousuke Yabuwaki, Shigeo Abe: Convergence improvement of active set support vector training. IJCNN 2010: 1-5

Seiichi Ozawa, Yohei Takeuchi, Shigeo Abe: A Fast Incremental Kernel Principal Component Analysis for Online Feature Extraction. PRICAI 2010: 487-497

Yusuke Torii, Shigeo Abe: Decomposition techniques for training linear programming support vector machines. Neurocomputing 72(4-6): 973-984 (2009)

Tao Ban, Changshui Zhang, Shigeo Abe: A new approach to discover interlacing data structures in high-dimensional space. J. Intell. Inf. Syst. 33(1): 3-22 (2009)

Kazuya Morikawa, Seiichi Ozawa, Shigeo Abe: Tuning membership functions of kernel fuzzy classifiers by maximizing margins. Memetic Computing 1(3): 221-228 (2009)

Takuya Kitamura, Syogo Takeuchi, Shigeo Abe, Kazuhiro Fukui: Subspace-based support vector machines for pattern classification. Neural Networks 22(5-6): 558-567 (2009)

Kazuki Iwamura, Shigeo Abe: Sparse support vector machines by kernel discriminant analysis. ESANN 2009

Shigeo Abe: Is Primal Better Than Dual. ICANN (1) 2009: 854-863

Tao Ban, Youki Kadobayashi, Shigeo Abe: Sparse kernel feature analysis using FastMap and its variants. IJCNN 2009: 256-263

Takuya Kitamura, Shigeo Abe, Kazuhiro Fukui: Subspace based least squares support vector machines for pattern classification. IJCNN 2009: 1640-1646

Shigenori Muraoka, Shigeo Abe: Sparse support vector regressors based on forward basis selection. IJCNN 2009: 2183-2187

Syogo Takeuchi, Takuya Kitamura, Shigeo Abe, Kazuhiro Fukui: Subspace based linear programming support vector machines. IJCNN 2009: 3067-3073

Shigeo Abe: Sparse Least Squares Support Vector Machines by Forward Selection Based on Linear Discriminant Analysis. ANNPR 2008: 54-65

Shigeo Abe: Comparison of sparse least squares support vector regressors trained in primal and dual. ESANN 2008: 469-474

Shigeo Abe: Batch Support Vector Training Based on Exact Incremental Training. ICANN (1) 2008: 295-304

Kazuya Morikawa, Shigeo Abe: Improved Parameter Tuning Algorithms for Fuzzy Classifiers. ICONIP (1) 2008: 937-944

Kazuki Iwamura, Shigeo Abe: Sparse support vector machines trained in the reduced empirical feature space. IJCNN 2008: 2398-2404

Tsuneyoshi Ishii, Shigeo Abe: Feature selection based on kernel discriminant analysis for multi-class problems. IJCNN 2008: 2455-2460

Shinji Kita, Seiichi Ozawa, Satoshi Maekawa, Shigeo Abe: A Learning Algorithm of Boosting Kernel Discriminant Analysis for Pattern Recognition. IEICE Transactions 90-D(11): 1853-1863 (2007)

Shigeo Abe: Sparse least squares support vector training in the reduced empirical feature space. Pattern Anal. Appl. 10(3): 203-214 (2007)

Shigeo Abe: Optimizing kernel parameters by second-order methods. ESANN 2007: 259-264

Ryota Hosokawa, Shigeo Abe: Fuzzy Classifiers Based on Kernel Discriminant Analysis. ICANN (2) 2007: 180-189

Shigeo Abe, Kenta Onishi: Sparse Least Squares Support Vector Regressors Trained in the Reduced Empirical Feature Space. ICANN (2) 2007: 527-536

Takashi Nagatani, Shigeo Abe: Backward Varilable Selection of Support Vector Regressors by Block Deletion. IJCNN 2007: 2117-2122

Yohei Takeuchi, Seiichi Ozawa, Shigeo Abe: An Efficient Incremental Kernel Principal Component Analysis for Online Feature Selection. IJCNN 2007: 2346-2351

Shinya Katagiri, Shigeo Abe: Incremental training of support vector machines using hyperspheres. Pattern Recognition Letters 27(13): 1495-1507 (2006)

Yuya Kamada, Shigeo Abe: Support Vector Regression Using Mahalanobis Kernels. ANNPR 2006: 144-152

Shinya Katagiri, Shigeo Abe: Incremental Training of Support Vector Machines Using Truncated Hypercones. ANNPR 2006: 153-164

Yusuke Torii, Shigeo Abe: Fast Training of Linear Programming Support Vector Machines Using Decomposition Techniques. ANNPR 2006: 165-176

Masamichi Ashihara, Shigeo Abe: Feature Selection Based on Kernel Discriminant Analysis. ICANN (2) 2006: 282-291

Tao Ban, Shigeo Abe: Implementing Multi-class Classifiers by One-class Classification Methods. IJCNN 2006: 327-332

Takuya Kidera, Seiichi Ozawa, Shigeo Abe: An Incremental Learning Algorithm of Ensemble Classifier Systems. IJCNN 2006: 3421-3427

Seiichi Ozawa, Soon Lee Toh, Shigeo Abe, Shaoning Pang, Nikola Kasabov: Incremental learning of feature space and classifier for face recognition. Neural Networks 18(5-6): 575-584 (2005)

Tomonori Kikuchi, Shigeo Abe: Comparison between error correcting output codes and fuzzy support vector machines. Pattern Recognition Letters 26(12): 1937-1945 (2005)

Shosuke Kimura, Seiichi Ozawa, Shigeo Abe: Incremental Kernel PCA for Online Learning of Feature Space. CIMCA/IAWTIC 2005: 595-600

Noriaki Kawamura, Motohide Yoshimura, Shigeo Abe: Image Query by Multiresolution Spectral Histograms. CIMCA/IAWTIC 2005: 660-665

Kohei Asano, Motohide Yoshimura, Shigeo Abe: Detection of Cell Forms in Multicellular Objects. CIMCA/IAWTIC 2005: 793-798

Takashi Iwai, Motohide Yoshimura, Shigeo Abe: Detection of Protein Crystallizations under Dynamic Environment. CIMCA/IAWTIC 2005: 1121-1127

Shigeo Abe: Modified backward feature selection by cross validation. ESANN 2005: 163-168

Shigeo Abe: Training of Support Vector Machines with Mahalanobis Kernels. ICANN (2) 2005: 571-576

Shinya Katagiri, Shigeo Abe: Selecting Support Vector Candidates for Incremental Training. SMC 2005: 1258-1263

Kenichi Kaieda, Shigeo Abe: KPCA-based training of a kernel fuzzy classifier with ellipsoidal regions. Int. J. Approx. Reasoning 37(3): 189-217 (2004)

Shigeo Abe: Fuzzy LP-SVMs for Multiclass Problems. ESANN 2004: 429-434

Daisuke Tsujinishi, Shigeo Abe: Fuzzy least squares support vector machines for multiclass problems. Neural Networks 16(5-6): 785-792 (2003)

Shigeo Abe, Takuya Inoue: Fuzzy support vector machines for multiclass problems. ESANN 2002: 113-118

Motohide Yoshimura, Hajime Kiyose, Shigeo Abe: Advanced Image Retrieval Using Multi-resolution Image Content. MVA 2002: 330-333

Shigeo Abe, Keita Sakaguchi: Generalization Improvement of a Fuzzy Classifier With Ellipsodial Regions. FUZZ-IEEE 2001: 207-210

Shigeo Abe, Takuya Inoue: Fast Training of Support Vector Machines by Extracting Boundary Data. ICANN 2001: 308-313

Shigeo Abe: Generalization Improvement of a Fuzzy Classifier with Pyramidal Membership Functions. ICPR 2000: 2211-2214

Hiroyasu Kubota, Hisashi Tamaki, Shigeo Abe: Robust Function Approximation Using Fuzzy Rules with Ellipsoidal Regions. IJCNN (6) 2000: 529-534

Kota Kawaratani, Shigeo Abe: Fast Feature Selection by Analyzing Class Regions Approximated by Ellipsoids. IJCNN (3) 2000: 549-554

Naoki Tsuchiya, Seiichi Ozawa, Shigeo Abe: Training Three-Layer Neural Network Classifiers by Solving Inequalities. IJCNN (3) 2000: 555-560

Shigeo Abe, Ruck Thawonmas, Masahiro Kayama: A fuzzy classifier with ellipsoidal regions for diagnosis problems. IEEE Transactions on Systems, Man, and Cybernetics, Part C 29(1): 140-148 (1999)

Ruck Thawonmas, Shigeo Abe: Function approximation based on fuzzy rules extracted from partitioned numerical data. IEEE Transactions on Systems, Man, and Cybernetics, Part B 29(4): 525-534 (1999)

Shigeo Abe, Ruck Thawonmas, Yoshiki Kobayashi: Feature selection by analyzing class regions approximated by ellipsoids. IEEE Transactions on Systems, Man, and Cybernetics, Part C 28(2): 282-287 (1998)

Ruck Thawonmas, Shigeo Abe: Rule acquisition based on hyperbox representation and its applications. KES (1) 1998: 120-125

Shigeo Abe: Training of a fuzzy classifier with ellipsoidal regions by dynamic cluster generation. KES (1) 1998: 126-131

Shigeo Abe, Ruck Thawonmas: A fuzzy classifier with ellipsoidal regions. IEEE T. Fuzzy Systems 5(3): 358-368 (1997)

Ruck Thawonmas, Shigeo Abe: A novel approach to feature selection based on analysis of class regions. IEEE Transactions on Systems, Man, and Cybernetics, Part B 27(2): 196-207 (1997)

Shigeo Abe, Ming-Shong Lan, Ruck Thawonmas: Tuning of a fuzzy classifier derived from data. Int. J. Approx. Reasoning 14(1): 1-24 (1996)

Takeshi Inoue, Shigeo Abe, Masahiro Kayama: LSI module placement using the kohonen network. Systems and Computers in Japan 27(6): 92-105 (1996)

Shigeo Abe: Convergence acceleration of the Hopfield neural network by optimizing integration step sizes. IEEE Transactions on Systems, Man, and Cybernetics, Part B 26(1): 194-201 (1996)

Shigeo Abe, Ming-Shong Lan: A method for fuzzy rules extraction directly from numerical data and its application to pattern classification. IEEE T. Fuzzy Systems 3(1): 18-28 (1995)

Shigeo Abe, Ming-Shong Lan: Fuzzy rules extraction directly from numerical data for function approximation. IEEE Transactions on Systems, Man, and Cybernetics 25(1): 119-129 (1995)

Volkmar Uebele, Shigeo Abe, Ming-Shong Lan: A neural-network-based fuzzy classifier. IEEE Transactions on Systems, Man, and Cybernetics 25(2): 353-361 (1995)

Shigeo Abe: Fuzzy Systems with Learning Capability. Fuzzy Logic in Artificial Intelligence 1995: 101-115

Masahiro Kayama, Shigeo Abe: Training neural net classifier to improve generalization capability. Systems and Computers in Japan 25(2): 101-110 (1994)

Shigeo Abe, Masahiro Kayama, Hiroshi Takenaga, Tadaaki Kitamura: Extracting algorithms from pattern classification neural networks. Neural Networks 6(5): 729-735 (1993)

Shigeo Abe, Junzo Kawakami, Kotaro Hirasawa: Solving inequality constrained combinatorial optimization problems by the hopfield neural networks. Neural Networks 5(4): 663-670 (1992)

Hiroshi Takenaga, Shigeo Abe, Masao Takatoo, Masahiro Kayama, Tadaaki Kitamura, Yosiyuki Okuyama: Optimal Input Selection of Neural Networks by Sensitivity Analysis and Its Application to Image Recognition. MVA 1990: 117-120

Ken-ichi Kurosawa, S. Yamaguchi, Shigeo Abe, Tadaaki Bandoh: Instruction Architecture for a High Performance Integrated Prolog Processor IPP. ICLP/SLP 1988: 1506-1530

Shigeo Abe, Tadaaki Bandoh, S. Yamaguchi, Ken-ichi Kurosawa, Kaori Kiriyama: High Performance Integrated Prolog Processor IPP. ISCA 1987: 100-107

Shigeo Abe, Ken-ichi Kurosawa, Kaori Kiriyama: A New Optimization Technique for a Prolog Computer. COMPCON 1986: 241-245

Shigeo Abe, Ryosei Hiraoka, Yasushi Fukunaga, Tadaaki Bandoh, Kotaro Hirasawa, Yukio Kawamoto: Preliminary Performance Evaluation of Data Flow Computers. COMPCON 1982: 224-227