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| 2011 | ||
|---|---|---|
| 77 | Shigeo Abe: Fast Support Vector Training by Newton's Method. ICANN (2) 2011: 143-150 | |
| 76 | Tao Ban, Changshui Zhang, Shigeo Abe, Takeshi Takahashi, Youki Kadobayashi: Mining interlacing manifolds in high dimensional spaces. SAC 2011: 942-949 | |
| 2010 | ||
| 75 | Tsuneyoshi Ishii, Shigeo Abe: Evaluation of Feature Selection by Multiclass Kernel Discriminant Analysis. ANNPR 2010: 13-24 | |
| 74 | Shigeo Abe: Active set training of support vector regressors. ESANN 2010 | |
| 73 | Shigeo Abe, Ryousuke Yabuwaki: Convergence Improvement of Active Set Training for Support Vector Regressors. ICANN (2) 2010: 1-10 | |
| 72 | Yasuyuki Tajiri, Ryousuke Yabuwaki, Takuya Kitamura, Shigeo Abe: Feature Extraction Using Support Vector Machines. ICONIP (2) 2010: 108-115 | |
| 71 | Ryousuke Yabuwaki, Shigeo Abe: Convergence improvement of active set support vector training. IJCNN 2010: 1-5 | |
| 70 | Takuya Kitamura, Syogo Takeuchi, Shigeo Abe: Feature selection and fast training of subspace based support vector machines. IJCNN 2010: 1-6 | |
| 69 | Seiichi Ozawa, Yohei Takeuchi, Shigeo Abe: A Fast Incremental Kernel Principal Component Analysis for Online Feature Extraction. PRICAI 2010: 487-497 | |
| 68 | Takashi Nagatani, Seiichi Ozawa, Shigeo Abe: Fast Variable Selection by Block Addition and Block Deletion. JILSA 2(4): 200-211 (2010) | |
| 2009 | ||
| 67 | Kazuki Iwamura, Shigeo Abe: Sparse support vector machines by kernel discriminant analysis. ESANN 2009 | |
| 66 | Shigeo Abe: Is Primal Better Than Dual. ICANN (1) 2009: 854-863 | |
| 65 | Takuya Kitamura, Shigeo Abe, Kazuhiro Fukui: Subspace based least squares support vector machines for pattern classification. IJCNN 2009: 1640-1646 | |
| 64 | Shigenori Muraoka, Shigeo Abe: Sparse support vector regressors based on forward basis selection. IJCNN 2009: 2183-2187 | |
| 63 | Tao Ban, Youki Kadobayashi, Shigeo Abe: Sparse kernel feature analysis using FastMap and its variants. IJCNN 2009: 256-263 | |
| 62 | Syogo Takeuchi, Takuya Kitamura, Shigeo Abe, Kazuhiro Fukui: Subspace based linear programming support vector machines. IJCNN 2009: 3067-3073 | |
| 61 | 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) | |
| 60 | Kazuya Morikawa, Seiichi Ozawa, Shigeo Abe: Tuning membership functions of kernel fuzzy classifiers by maximizing margins. Memetic Computing 1(3): 221-228 (2009) | |
| 59 | Takuya Kitamura, Syogo Takeuchi, Shigeo Abe, Kazuhiro Fukui: Subspace-based support vector machines for pattern classification. Neural Networks 22(5-6): 558-567 (2009) | |
| 58 | Yusuke Torii, Shigeo Abe: Decomposition techniques for training linear programming support vector machines. Neurocomputing 72(4-6): 973-984 (2009) | |
| 2008 | ||
| 57 | Shigeo Abe: Sparse Least Squares Support Vector Machines by Forward Selection Based on Linear Discriminant Analysis. ANNPR 2008: 54-65 | |
| 56 | Shigeo Abe: Comparison of sparse least squares support vector regressors trained in primal and dual. ESANN 2008: 469-474 | |
| 55 | Shigeo Abe: Batch Support Vector Training Based on Exact Incremental Training. ICANN (1) 2008: 295-304 | |
| 54 | Kazuya Morikawa, Shigeo Abe: Improved Parameter Tuning Algorithms for Fuzzy Classifiers. ICONIP (1) 2008: 937-944 | |
| 53 | Kazuki Iwamura, Shigeo Abe: Sparse support vector machines trained in the reduced empirical feature space. IJCNN 2008: 2398-2404 | |
| 52 | Tsuneyoshi Ishii, Shigeo Abe: Feature selection based on kernel discriminant analysis for multi-class problems. IJCNN 2008: 2455-2460 | |
| 2007 | ||
| 51 | Shigeo Abe: Optimizing kernel parameters by second-order methods. ESANN 2007: 259-264 | |
| 50 | Ryota Hosokawa, Shigeo Abe: Fuzzy Classifiers Based on Kernel Discriminant Analysis. ICANN (2) 2007: 180-189 | |
| 49 | Shigeo Abe, Kenta Onishi: Sparse Least Squares Support Vector Regressors Trained in the Reduced Empirical Feature Space. ICANN (2) 2007: 527-536 | |
| 48 | Takashi Nagatani, Shigeo Abe: Backward Varilable Selection of Support Vector Regressors by Block Deletion. IJCNN 2007: 2117-2122 | |
| 47 | Yohei Takeuchi, Seiichi Ozawa, Shigeo Abe: An Efficient Incremental Kernel Principal Component Analysis for Online Feature Selection. IJCNN 2007: 2346-2351 | |
| 46 | 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) | |
| 45 | Shigeo Abe: Sparse least squares support vector training in the reduced empirical feature space. Pattern Anal. Appl. 10(3): 203-214 (2007) | |
| 2006 | ||
| 44 | Yuya Kamada, Shigeo Abe: Support Vector Regression Using Mahalanobis Kernels. ANNPR 2006: 144-152 | |
| 43 | Shinya Katagiri, Shigeo Abe: Incremental Training of Support Vector Machines Using Truncated Hypercones. ANNPR 2006: 153-164 | |
| 42 | Yusuke Torii, Shigeo Abe: Fast Training of Linear Programming Support Vector Machines Using Decomposition Techniques. ANNPR 2006: 165-176 | |
| 41 | Masamichi Ashihara, Shigeo Abe: Feature Selection Based on Kernel Discriminant Analysis. ICANN (2) 2006: 282-291 | |
| 40 | Tao Ban, Shigeo Abe: Implementing Multi-class Classifiers by One-class Classification Methods. IJCNN 2006: 327-332 | |
| 39 | Takuya Kidera, Seiichi Ozawa, Shigeo Abe: An Incremental Learning Algorithm of Ensemble Classifier Systems. IJCNN 2006: 3421-3427 | |
| 38 | Shinya Katagiri, Shigeo Abe: Incremental training of support vector machines using hyperspheres. Pattern Recognition Letters 27(13): 1495-1507 (2006) | |
| 2005 | ||
| 37 | Takashi Iwai, Motohide Yoshimura, Shigeo Abe: Detection of Protein Crystallizations under Dynamic Environment. CIMCA/IAWTIC 2005: 1121-1127 | |
| 36 | Shosuke Kimura, Seiichi Ozawa, Shigeo Abe: Incremental Kernel PCA for Online Learning of Feature Space. CIMCA/IAWTIC 2005: 595-600 | |
| 35 | Noriaki Kawamura, Motohide Yoshimura, Shigeo Abe: Image Query by Multiresolution Spectral Histograms. CIMCA/IAWTIC 2005: 660-665 | |
| 34 | Kohei Asano, Motohide Yoshimura, Shigeo Abe: Detection of Cell Forms in Multicellular Objects. CIMCA/IAWTIC 2005: 793-798 | |
| 33 | Shigeo Abe: Modified backward feature selection by cross validation. ESANN 2005: 163-168 | |
| 32 | Shigeo Abe: Training of Support Vector Machines with Mahalanobis Kernels. ICANN (2) 2005: 571-576 | |
| 31 | 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) | |
| 30 | Tomonori Kikuchi, Shigeo Abe: Comparison between error correcting output codes and fuzzy support vector machines. Pattern Recognition Letters 26(12): 1937-1945 (2005) | |
| 2004 | ||
| 29 | Shigeo Abe: Fuzzy LP-SVMs for Multiclass Problems. ESANN 2004: 429-434 | |
| 28 | Kenichi Kaieda, Shigeo Abe: KPCA-based training of a kernel fuzzy classifier with ellipsoidal regions. Int. J. Approx. Reasoning 37(3): 189-217 (2004) | |
| 2003 | ||
| 27 | Daisuke Tsujinishi, Shigeo Abe: Fuzzy least squares support vector machines for multiclass problems. Neural Networks 16(5-6): 785-792 (2003) | |
| 2002 | ||
| 26 | Shigeo Abe, Takuya Inoue: Fuzzy support vector machines for multiclass problems. ESANN 2002: 113-118 | |
| 25 | Motohide Yoshimura, Hajime Kiyose, Shigeo Abe: Advanced Image Retrieval Using Multi-resolution Image Content. MVA 2002: 330-333 | |
| 2001 | ||
| 24 | Shigeo Abe, Keita Sakaguchi: Generalization Improvement of a Fuzzy Classifier With Ellipsodial Regions. FUZZ-IEEE 2001: 207-210 | |
| 23 | Shigeo Abe, Takuya Inoue: Fast Training of Support Vector Machines by Extracting Boundary Data. ICANN 2001: 308-313 | |
| 2000 | ||
| 22 | Shigeo Abe: Generalization Improvement of a Fuzzy Classifier with Pyramidal Membership Functions. ICPR 2000: 2211-2214 | |
| 21 | Kota Kawaratani, Shigeo Abe: Fast Feature Selection by Analyzing Class Regions Approximated by Ellipsoids. IJCNN (3) 2000: 549-554 | |
| 20 | Naoki Tsuchiya, Seiichi Ozawa, Shigeo Abe: Training Three-Layer Neural Network Classifiers by Solving Inequalities. IJCNN (3) 2000: 555-560 | |
| 19 | Hiroyasu Kubota, Hisashi Tamaki, Shigeo Abe: Robust Function Approximation Using Fuzzy Rules with Ellipsoidal Regions. IJCNN (6) 2000: 529-534 | |
| 1999 | ||
| 18 | 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) | |
| 17 | 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) | |
| 1998 | ||
| 16 | Ruck Thawonmas, Shigeo Abe: Rule acquisition based on hyperbox representation and its applications. KES (1) 1998: 120-125 | |
| 15 | Shigeo Abe: Training of a fuzzy classifier with ellipsoidal regions by dynamic cluster generation. KES (1) 1998: 126-131 | |
| 14 | 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) | |
| 1997 | ||
| 13 | 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) | |
| 1996 | ||
| 12 | 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) | |
| 11 | Shigeo Abe, Ming-Shong Lan, Ruck Thawonmas: Tuning of a fuzzy classifier derived from data. Int. J. Approx. Reasoning 14(1): 1-24 (1996) | |
| 1995 | ||
| 10 | Shigeo Abe: Fuzzy Systems with Learning Capability. Fuzzy Logic in Artificial Intelligence 1995: 101-115 | |
| 9 | 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) | |
| 8 | 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) | |
| 1993 | ||
| 7 | Shigeo Abe, Masahiro Kayama, Hiroshi Takenaga, Tadaaki Kitamura: Extracting algorithms from pattern classification neural networks. Neural Networks 6(5): 729-735 (1993) | |
| 1992 | ||
| 6 | Shigeo Abe, Junzo Kawakami, Kotaro Hirasawa: Solving inequality constrained combinatorial optimization problems by the hopfield neural networks. Neural Networks 5(4): 663-670 (1992) | |
| 1990 | ||
| 5 | 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 | |
| 1988 | ||
| 4 | Ken-ichi Kurosawa, S. Yamaguchi, Shigeo Abe, Tadaaki Bandoh: Instruction Architecture for a High Performance Integrated Prolog Processor IPP. ICLP/SLP 1988: 1506-1530 | |
| 1987 | ||
| 3 | Shigeo Abe, Tadaaki Bandoh, S. Yamaguchi, Ken-ichi Kurosawa, Kaori Kiriyama: High Performance Integrated Prolog Processor IPP. ISCA 1987: 100-107 | |
| 1986 | ||
| 2 | Shigeo Abe, Ken-ichi Kurosawa, Kaori Kiriyama: A New Optimization Technique for a Prolog Computer. COMPCON 1986: 241-245 | |
| 1982 | ||
| 1 | Shigeo Abe, Ryosei Hiraoka, Yasushi Fukunaga, Tadaaki Bandoh, Kotaro Hirasawa, Yukio Kawamoto: Preliminary Performance Evaluation of Data Flow Computers. COMPCON 1982: 224-227 | |
Colors in the list of coauthors
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