Shigeo Abe

ORCID

Publication Activity (10 Years)

Years Active: 1982-2023
Publications (10 Years): 12

Top Venues

ANNPR

IJCNN

Pattern Recognit. Lett.

SMC

Publications

Shigeo Abe
Training Minimal Complexity Support Vector Machines with Multiple Kernels. SMC (2023)
Shigeo Abe
Soft Upper-bound Support Vector Machines. IJCNN (2022)
Shigeo Abe
Do Minimal Complexity Least Squares Support Vector Machines Work? ANNPR (2022)
Shigeo Abe
Soft Upper-bound Minimal Complexity LP SVMs. IJCNN (2021)
Shigeo Abe
Minimal Complexity Support Vector Machines for Pattern Classification. Comput. 9 (4) (2020)
Shigeo Abe
Minimal Complexity Support Vector Machines. ANNPR (2020)
Shigeo Abe
Analyzing Minimal Complexity Machines. IJCNN (2019)
Shigeo Abe
Are twin hyperplanes necessary? Pattern Recognit. Lett. 116 (2018)
Shigeo Abe
Effect of Equality Constraints to Unconstrained Large Margin Distribution Machines. ANNPR (2018)
Shigeo Abe
Unconstrained large margin distribution machines. Pattern Recognit. Lett. 98 (2017)
Shigeo Abe
Improving Generalization Abilities of Maximal Average Margin Classifiers. ANNPR (2016)
Shigeo Abe
Fusing sequential minimal optimization and Newton's method for support vector training. Int. J. Mach. Learn. Cybern. 7 (3) (2016)
Shigeo Abe
Optimizing working sets for training support vector regressors by Newton's method. IJCNN (2015)
Shigeo Abe
Fuzzy support vector machines for multilabel classification. Pattern Recognit. 48 (6) (2015)
Shigeo Abe
Incremental Feature Selection by Block Addition and Block Deletion Using Least Squares SVRs. ANNPR (2014)
Shigeo Abe
Incremental Input Variable Selection by Block Addition and Block Deletion. ICANN (2014)
Shigeo Abe
Feature Selection by Iterative Block Addition and Block Deletion. SMC (2013)
Takashi Nagatani, Shigeo Abe
Feature Selection by Block Addition and Block Deletion. ANNPR (2012)
Shigeo Abe
Training Mahalanobis Kernels by Linear Programming. ICANN (2) (2012)
Shigeo Abe
Fast Support Vector Training by Newton's Method. ICANN (2) (2011)
Takuya Kitamura, Shigeo Abe, Yusuke Tanaka
Multiple Nonlinear Subspace Methods Using Subspace-based Support Vector Machines. ICMLA (1) (2011)
Tao Ban, Changshui Zhang, Shigeo Abe, Takeshi Takahashi, Youki Kadobayashi
Mining interlacing manifolds in high dimensional spaces. SAC (2011)
Shigeo Abe
Active set training of support vector regressors. ESANN (2010)
Seiichi Ozawa, Yohei Takeuchi, Shigeo Abe
A Fast Incremental Kernel Principal Component Analysis for Online Feature Extraction. PRICAI (2010)
Takashi Nagatani, Seiichi Ozawa, Shigeo Abe
Fast Variable Selection by Block Addition and Block Deletion. J. Intell. Learn. Syst. Appl. 2 (4) (2010)
Yasuyuki Tajiri, Ryousuke Yabuwaki, Takuya Kitamura, Shigeo Abe
Feature Extraction Using Support Vector Machines. ICONIP (2) (2010)
Tsuneyoshi Ishii, Shigeo Abe
Evaluation of Feature Selection by Multiclass Kernel Discriminant Analysis. ANNPR (2010)
Shigeo Abe, Ryousuke Yabuwaki
Convergence Improvement of Active Set Training for Support Vector Regressors. ICANN (2) (2010)
Takuya Kitamura, Syogo Takeuchi, Shigeo Abe
Feature selection and fast training of subspace based support vector machines. IJCNN (2010)
Takuya Kitamura, Shigeo Abe
Subspace-Based L2 Support Vector Machines. Aust. J. Intell. Inf. Process. Syst. 12 (3) (2010)
Ryousuke Yabuwaki, Shigeo Abe
Convergence improvement of active set support vector training. IJCNN (2010)
Shigeo Abe
Is Primal Better Than Dual. ICANN (1) (2009)
Takuya Kitamura, Shigeo Abe, Kazuhiro Fukui
Subspace based least squares support vector machines for pattern classification. IJCNN (2009)
Kazuya Morikawa, Seiichi Ozawa, Shigeo Abe
Tuning membership functions of kernel fuzzy classifiers by maximizing margins. Memetic Comput. 1 (3) (2009)
Syogo Takeuchi, Takuya Kitamura, Shigeo Abe, Kazuhiro Fukui
Subspace based linear programming support vector machines. IJCNN (2009)
Shigenori Muraoka, Shigeo Abe
Sparse support vector regressors based on forward basis selection. IJCNN (2009)
Kazuki Iwamura, Shigeo Abe
Sparse support vector machines by kernel discriminant analysis. ESANN (2009)
Yusuke Torii, Shigeo Abe
Decomposition techniques for training linear programming support vector machines. Neurocomputing 72 (4-6) (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) (2009)
Takuya Kitamura, Syogo Takeuchi, Shigeo Abe, Kazuhiro Fukui
Subspace-based support vector machines for pattern classification. Neural Networks 22 (5-6) (2009)
Tao Ban, Youki Kadobayashi, Shigeo Abe
Sparse kernel feature analysis using FastMap and its variants. IJCNN (2009)
Kazuya Morikawa, Shigeo Abe
Improved Parameter Tuning Algorithms for Fuzzy Classifiers. ICONIP (1) (2008)
Kazuki Iwamura, Shigeo Abe
Sparse support vector machines trained in the reduced empirical feature space. IJCNN (2008)
Tsuneyoshi Ishii, Shigeo Abe
Feature selection based on kernel discriminant analysis for multi-class problems. IJCNN (2008)
Tsuneyoshi Ishii, Masamichi Ashihara, Shigeo Abe
Kernel discriminant analysis based feature selection. Neurocomputing 71 (13-15) (2008)
Shigeo Abe
Sparse Least Squares Support Vector Machines by Forward Selection Based on Linear Discriminant Analysis. ANNPR (2008)
Shigeo Abe
Comparison of sparse least squares support vector regressors trained in primal and dual. ESANN (2008)
Shigeo Abe
Batch Support Vector Training Based on Exact Incremental Training. ICANN (1) (2008)
Shigeo Abe
Sparse least squares support vector training in the reduced empirical feature space. Pattern Anal. Appl. 10 (3) (2007)
Ryota Hosokawa, Shigeo Abe
Fuzzy Classifiers Based on Kernel Discriminant Analysis. ICANN (2) (2007)
Yohei Takeuchi, Seiichi Ozawa, Shigeo Abe
An Efficient Incremental Kernel Principal Component Analysis for Online Feature Selection. IJCNN (2007)
Shinji Kita, Seiichi Ozawa, Satoshi Maekawa, Shigeo Abe
A Learning Algorithm of Boosting Kernel Discriminant Analysis for Pattern Recognition. IEICE Trans. Inf. Syst. (11) (2007)
Takashi Nagatani, Shigeo Abe
Backward Varilable Selection of Support Vector Regressors by Block Deletion. IJCNN (2007)
Shigeo Abe, Kenta Onishi
Sparse Least Squares Support Vector Regressors Trained in the Reduced Empirical Feature Space. ICANN (2) (2007)
Shigeo Abe
Optimizing kernel parameters by second-order methods. ESANN (2007)
Masamichi Ashihara, Shigeo Abe
Feature Selection Based on Kernel Discriminant Analysis. ICANN (2) (2006)
Shinya Katagiri, Shigeo Abe
Incremental Training of Support Vector Machines Using Truncated Hypercones. ANNPR (2006)
Yuya Kamada, Shigeo Abe
Support Vector Regression Using Mahalanobis Kernels. ANNPR (2006)
Tao Ban, Shigeo Abe
Implementing Multi-class Classifiers by One-class Classification Methods. IJCNN (2006)
Takuya Kidera, Seiichi Ozawa, Shigeo Abe
An Incremental Learning Algorithm of Ensemble Classifier Systems. IJCNN (2006)
Shinya Katagiri, Shigeo Abe
Incremental training of support vector machines using hyperspheres. Pattern Recognit. Lett. 27 (13) (2006)
Yusuke Torii, Shigeo Abe
Fast Training of Linear Programming Support Vector Machines Using Decomposition Techniques. ANNPR (2006)
Seiichi Ozawa, Soon Lee Toh, Shigeo Abe, Shaoning Pang, Nikola K. Kasabov
Incremental learning of feature space and classifier for face recognition. Neural Networks 18 (5-6) (2005)
Noriaki Kawamura, Motohide Yoshimura, Shigeo Abe
Image Query by Multiresolution Spectral Histograms. CIMCA/IAWTIC (2005)
Tomonori Kikuchi, Shigeo Abe
Comparison between error correcting output codes and fuzzy support vector machines. Pattern Recognit. Lett. 26 (12) (2005)
Shigeo Abe
Modified backward feature selection by cross validation. ESANN (2005)
Shigeo Abe
Training of Support Vector Machines with Mahalanobis Kernels. ICANN (2) (2005)
Shosuke Kimura, Seiichi Ozawa, Shigeo Abe
Incremental Kernel PCA for Online Learning of Feature Space. CIMCA/IAWTIC (2005)
Shinya Katagiri, Shigeo Abe
Selecting Support Vector Candidates for Incremental Training. SMC (2005)
Takashi Iwai, Motohide Yoshimura, Shigeo Abe
Detection of Protein Crystallizations under Dynamic Environment. CIMCA/IAWTIC (2005)
Kohei Asano, Motohide Yoshimura, Shigeo Abe
Detection of Cell Forms in Multicellular Objects. CIMCA/IAWTIC (2005)
Kenichi Kaieda, Shigeo Abe
KPCA-based training of a kernel fuzzy classifier with ellipsoidal regions. Int. J. Approx. Reason. 37 (3) (2004)
Shigeo Abe
Fuzzy LP-SVMs for Multiclass Problems. ESANN (2004)
Daisuke Tsujinishi, Shigeo Abe
Fuzzy least squares support vector machines for multiclass problems. Neural Networks 16 (5-6) (2003)
Shigeo Abe
Analysis of support vector machines. NNSP (2002)
Motohide Yoshimura, Hajime Kiyose, Shigeo Abe
Advanced Image Retrieval Using Multi-resolution Image Content. MVA (2002)
Shigeo Abe, Takuya Inoue
Fuzzy support vector machines for multiclass problems. ESANN (2002)
Shigeo Abe, Keita Sakaguchi
Generalization Improvement of a Fuzzy Classifier With Ellipsodial Regions. FUZZ-IEEE (2001)
Shigeo Abe, Takuya Inoue
Fast Training of Support Vector Machines by Extracting Boundary Data. ICANN (2001)
Kota Kawaratani, Shigeo Abe
Fast Feature Selection by Analyzing Class Regions Approximated by Ellipsoids. IJCNN (3) (2000)
Hiroyasu Kubota, Hisashi Tamaki, Shigeo Abe
Robust Function Approximation Using Fuzzy Rules with Ellipsoidal Regions. IJCNN (6) (2000)
Shigeo Abe
Generalization Improvement of a Fuzzy Classifier with Pyramidal Membership Functions. ICPR (2000)
Naoki Tsuchiya, Seiichi Ozawa, Shigeo Abe
Training Three-Layer Neural Network Classifiers by Solving Inequalities. IJCNN (3) (2000)
Ruck Thawonmas, Shigeo Abe
Function approximation based on fuzzy rules extracted from partitioned numerical data. IEEE Trans. Syst. Man Cybern. Part B 29 (4) (1999)
Hisashi Tamaki, Etsuo Nishino, Shigeo Abe
A genetic algorithm approach to multi-objective scheduling problems with earliness and tardiness penalties. CEC (1999)
Shigeo Abe
Fuzzy function approximators with ellipsoidal regions. IEEE Trans. Syst. Man Cybern. Part B 29 (5) (1999)
Shigeo Abe, Ruck Thawonmas, Masahiro Kayama
A fuzzy classifier with ellipsoidal regions for diagnosis problems. IEEE Trans. Syst. Man Cybern. Part C 29 (1) (1999)
Shigeo Abe
Dynamic cluster generation for a fuzzy classifier with ellipsoidal regions. IEEE Trans. Syst. Man Cybern. Part B 28 (6) (1998)
Shigeo Abe, Ruck Thawonmas, Yoshiki Kobayashi
Feature selection by analyzing class regions approximated by ellipsoids. IEEE Trans. Syst. Man Cybern. Part C 28 (2) (1998)
Shigeo Abe
Training of a fuzzy classifier with ellipsoidal regions by dynamic cluster generation. KES (1) (1998)
Ruck Thawonmas, Shigeo Abe
Rule acquisition based on hyperbox representation and its applications. KES (1) (1998)
Ruck Thawonmas, Shigeo Abe
A novel approach to feature selection based on analysis of class regions. IEEE Trans. Syst. Man Cybern. Part B 27 (2) (1997)
Ruck Thawonmas, Shigeo Abe
Function Approximation with Partitioned Ellipsoidal Regions. ICONIP (1) (1997)
Shigeo Abe, Ruck Thawonmas
A fuzzy classifier with ellipsoidal regions. IEEE Trans. Fuzzy Syst. 5 (3) (1997)
Ruck Thawonmas, Shigeo Abe
Extraction of Fuzzy Rules for Classification Based on Partitioned Hyperboxes. J. Intell. Fuzzy Syst. 4 (3) (1996)
Takeshi Inoue, Shigeo Abe, Masahiro Kayama
LSI module placement using the kohonen network. Systems and Computers in Japan 27 (6) (1996)
Ruck Thawonmas, Shigeo Abe
A fuzzy classifier based on partitioned hyperboxes. ICNN (1996)
Shigeo Abe
Convergence acceleration of the Hopfield neural network by optimizing integration step sizes. IEEE Trans. Syst. Man Cybern. Part B 26 (1) (1996)
Shigeo Abe, Ming-Shong Lan, Ruck Thawonmas
Tuning of a fuzzy classifier derived from data. Int. J. Approx. Reason. 14 (1) (1996)
Ruck Thawonmas, Shigeo Abe
Feature reduction based on analysis of fuzzy regions. ICNN (1995)

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Publication Activity (10 Years)

Top Topics

Top Venues

Shigeo Abe