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

A New Optimization Technique for a Prolog Computer. - Shigeo Abe; Ken-ichi Kurosawa; Kaori Kiriyama (COMPCON, 1986)

High Performance Integrated Prolog Processor IPP. - Shigeo Abe; Tadaaki Bandoh; S. Yamaguchi; Ken-ichi Kurosawa; Kaori Kiriyama (ISCA, 1987)

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

Learning by parallel forward propagation. - Shigeo Abe (IJCNN, 1990)

Convergence of the Hopfield neural networks with inequality constraints. - Shigeo Abe (IJCNN, 1990)

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

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

Extracting algorithms from pattern classification neural networks. - Shigeo Abe; Masahiro Kayama; Hiroshi Takenaga; Tadaaki Kitamura (Neural Networks, 1993)

Training neural net classifier to improve generalization capability. - Masahiro Kayama; Shigeo Abe (Syst. Comput. Jpn., 1994)

Feature reduction based on analysis of fuzzy regions. - Ruck Thawonmas; Shigeo Abe (ICNN, 1995)

Fuzzy Systems with Learning Capability. - Shigeo Abe (Fuzzy Logic in Artificial Intelligence, 1995)

A method for fuzzy rules extraction directly from numerical data and its application to pattern classification. - Shigeo Abe; Ming-Shong Lan (IEEE Trans. Fuzzy Syst., 1995)

Fuzzy rules extraction directly from numerical data for function approximation. - Shigeo Abe; Ming-Shong Lan (IEEE Trans. Syst. Man Cybern., 1995)

A neural-network-based fuzzy classifier. - Volkmar Uebele; Shigeo Abe; Ming-Shong Lan (IEEE Trans. Syst. Man Cybern., 1995)

A fuzzy classifier based on partitioned hyperboxes. - Ruck Thawonmas; Shigeo Abe (ICNN, 1996)

Tuning of a fuzzy classifier derived from data. - Shigeo Abe; Ming-Shong Lan; Ruck Thawonmas (Int. J. Approx. Reason., 1996)

Extraction of Fuzzy Rules for Classification Based on Partitioned Hyperboxes. - Ruck Thawonmas; Shigeo Abe (J. Intell. Fuzzy Syst., 1996)

LSI module placement using the kohonen network. - Takeshi Inoue; Shigeo Abe; Masahiro Kayama (Syst. Comput. Jpn., 1996)

Convergence acceleration of the Hopfield neural network by optimizing integration step sizes. - Shigeo Abe (IEEE Trans. Syst. Man Cybern. Part B, 1996)

Function Approximation with Partitioned Ellipsoidal Regions. - Ruck Thawonmas; Shigeo Abe (ICONIP (1), 1997)

A fuzzy classifier with ellipsoidal regions. - Shigeo Abe; Ruck Thawonmas (IEEE Trans. Fuzzy Syst., 1997)

A novel approach to feature selection based on analysis of class regions. - Ruck Thawonmas; Shigeo Abe (IEEE Trans. Syst. Man Cybern. Part B, 1997)

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

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

Dynamic cluster generation for a fuzzy classifier with ellipsoidal regions. - Shigeo Abe (IEEE Trans. Syst. Man Cybern. Part B, 1998)

Feature selection by analyzing class regions approximated by ellipsoids. - Shigeo Abe; Ruck Thawonmas; Yoshiki Kobayashi (IEEE Trans. Syst. Man Cybern. Part C, 1998)

A genetic algorithm approach to multi-objective scheduling problems with earliness and tardiness penalties. - Hisashi Tamaki; Etsuo Nishino; Shigeo Abe (CEC, 1999)

Fuzzy function approximators with ellipsoidal regions. - Shigeo Abe (IEEE Trans. Syst. Man Cybern. Part B, 1999)

A fuzzy classifier with ellipsoidal regions for diagnosis problems. - Shigeo Abe; Ruck Thawonmas; Masahiro Kayama (IEEE Trans. Syst. Man Cybern. Part C, 1999)

Function approximation based on fuzzy rules extracted from partitioned numerical data. - Ruck Thawonmas; Shigeo Abe (IEEE Trans. Syst. Man Cybern. Part B, 1999)

Generalization Improvement of a Fuzzy Classifier with Pyramidal Membership Functions. - Shigeo Abe (ICPR, 2000)

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

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

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

Generalization Improvement of a Fuzzy Classifier With Ellipsodial Regions. - Shigeo Abe; Keita Sakaguchi (FUZZ-IEEE, 2001)

Fast Training of Support Vector Machines by Extracting Boundary Data. - Shigeo Abe; Takuya Inoue (ICANN, 2001)

Fuzzy support vector machines for multiclass problems. - Shigeo Abe; Takuya Inoue (ESANN, 2002)

Advanced Image Retrieval Using Multi-resolution Image Content. - Motohide Yoshimura; Hajime Kiyose; Shigeo Abe (MVA, 2002)

Analysis of support vector machines. - Shigeo Abe (NNSP, 2002)

A kernel fuzzy classifier with ellipsoidal regions. - Kenichi Kaieda; Shigeo Abe (IJCNN, 2003)

Comparison of L1 and L2 support vector machines. - Yoshiaki Koshiba; Shigeo Abe (IJCNN, 2003)

A fast incremental learning algorithm of RBF networks with long-term memory. - Keisuke Okamoto; Seiichi Ozawa; Shigeo Abe (IJCNN, 2003)

Fuzzy least squares support vector machines. - Daisuke Tsujinishi; Shigeo Abe (IJCNN, 2003)

Fuzzy least squares support vector machines for multiclass problems. - Daisuke Tsujinishi; Shigeo Abe (Neural Networks, 2003)

Fuzzy LP-SVMs for Multiclass Problems. - Shigeo Abe (ESANN, 2004)

Spatially chunking support vector clustering algorithm. - Tao Ban; Shigeo Abe (IJCNN, 2004)

Why pairwise is better than one-against-all or all-at-once. - Daisuke Tsujinishi; Yoshiaki Koshiba; Shigeo Abe (IJCNN, 2004)

KPCA-based training of a kernel fuzzy classifier with ellipsoidal regions. - Kenichi Kaieda; Shigeo Abe (Int. J. Approx. Reason., 2004)

Detection of Cell Forms in Multicellular Objects. - Kohei Asano; Motohide Yoshimura; Shigeo Abe (CIMCA/IAWTIC, 2005)

Detection of Protein Crystallizations under Dynamic Environment. - Takashi Iwai; Motohide Yoshimura; Shigeo Abe (CIMCA/IAWTIC, 2005)

Image Query by Multiresolution Spectral Histograms. - Noriaki Kawamura; Motohide Yoshimura; Shigeo Abe (CIMCA/IAWTIC, 2005)

Incremental Kernel PCA for Online Learning of Feature Space. - Shosuke Kimura; Seiichi Ozawa; Shigeo Abe (CIMCA/IAWTIC, 2005)

Modified backward feature selection by cross validation. - Shigeo Abe (ESANN, 2005)

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

SVM ensembles for selecting the relevant feature subsets. - Tao Ban; Shigeo Abe (IJCNN, 2005)

Incremental learning for online face recognition. - Seiichi Ozawa; Soon Lee Toh; Shigeo Abe; Shaoning Pang 001; Nikola K. Kasabov (IJCNN, 2005)

Selecting Support Vector Candidates for Incremental Training. - Shinya Katagiri; Shigeo Abe (SMC, 2005)

Incremental learning of feature space and classifier for face recognition. - Seiichi Ozawa; Soon Lee Toh; Shigeo Abe; Shaoning Pang 001; Nikola K. Kasabov (Neural Networks, 2005)

Comparison between error correcting output codes and fuzzy support vector machines. - Tomonori Kikuchi; Shigeo Abe (Pattern Recognit. Lett., 2005)

Support Vector Machines for Pattern Classification. - Shigeo Abe (Springer, 2005)

Support Vector Regression Using Mahalanobis Kernels. - Yuya Kamada; Shigeo Abe (ANNPR, 2006)

Incremental Training of Support Vector Machines Using Truncated Hypercones. - Shinya Katagiri; Shigeo Abe (ANNPR, 2006)

Fast Training of Linear Programming Support Vector Machines Using Decomposition Techniques. - Yusuke Torii; Shigeo Abe (ANNPR, 2006)

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

Implementing Multi-class Classifiers by One-class Classification Methods. - Tao Ban; Shigeo Abe (IJCNN, 2006)

An Incremental Learning Algorithm of Ensemble Classifier Systems. - Takuya Kidera; Seiichi Ozawa; Shigeo Abe (IJCNN, 2006)

Incremental training of support vector machines using hyperspheres. - Shinya Katagiri; Shigeo Abe (Pattern Recognit. Lett., 2006)

Optimizing kernel parameters by second-order methods. - Shigeo Abe (ESANN, 2007)

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

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

Backward Varilable Selection of Support Vector Regressors by Block Deletion. - Takashi Nagatani; Shigeo Abe (IJCNN, 2007)

An Efficient Incremental Kernel Principal Component Analysis for Online Feature Selection. - Yohei Takeuchi; Seiichi Ozawa; Shigeo Abe (IJCNN, 2007)

A Learning Algorithm of Boosting Kernel Discriminant Analysis for Pattern Recognition. - Shinji Kita; Seiichi Ozawa; Satoshi Maekawa; Shigeo Abe (IEICE Trans. Inf. Syst., 2007)

Sparse least squares support vector training in the reduced empirical feature space. - Shigeo Abe (Pattern Anal. Appl., 2007)

Sparse Least Squares Support Vector Machines by Forward Selection Based on Linear Discriminant Analysis. - Shigeo Abe (ANNPR, 2008)

Comparison of sparse least squares support vector regressors trained in primal and dual. - Shigeo Abe (ESANN, 2008)

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

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

Feature selection based on kernel discriminant analysis for multi-class problems. - Tsuneyoshi Ishii; Shigeo Abe (IJCNN, 2008)

Sparse support vector machines trained in the reduced empirical feature space. - Kazuki Iwamura; Shigeo Abe (IJCNN, 2008)

Kernel discriminant analysis based feature selection. - Tsuneyoshi Ishii; Masamichi Ashihara; Shigeo Abe (Neurocomputing, 2008)

Sparse support vector machines by kernel discriminant analysis. - Kazuki Iwamura; Shigeo Abe (ESANN, 2009)

Is Primal Better Than Dual. - Shigeo Abe (ICANN (1), 2009)

Sparse kernel feature analysis using FastMap and its variants. - Tao Ban; Youki Kadobayashi; Shigeo Abe (IJCNN, 2009)

Subspace based least squares support vector machines for pattern classification. - Takuya Kitamura; Shigeo Abe; Kazuhiro Fukui (IJCNN, 2009)

Sparse support vector regressors based on forward basis selection. - Shigenori Muraoka; Shigeo Abe (IJCNN, 2009)

Subspace based linear programming support vector machines. - Syogo Takeuchi; Takuya Kitamura; Shigeo Abe; Kazuhiro Fukui (IJCNN, 2009)

Decomposition techniques for training linear programming support vector machines. - Yusuke Torii; Shigeo Abe (Neurocomputing, 2009)

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

Tuning membership functions of kernel fuzzy classifiers by maximizing margins. - Kazuya Morikawa; Seiichi Ozawa; Shigeo Abe (Memetic Comput., 2009)

Subspace-based support vector machines for pattern classification. - Takuya Kitamura; Syogo Takeuchi; Shigeo Abe; Kazuhiro Fukui (Neural Networks, 2009)

Evaluation of Feature Selection by Multiclass Kernel Discriminant Analysis. - Tsuneyoshi Ishii; Shigeo Abe (ANNPR, 2010)

Active set training of support vector regressors. - Shigeo Abe (ESANN, 2010)

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

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

Feature selection and fast training of subspace based support vector machines. - Takuya Kitamura; Syogo Takeuchi; Shigeo Abe (IJCNN, 2010)

Convergence improvement of active set support vector training. - Ryousuke Yabuwaki; Shigeo Abe (IJCNN, 2010)

A Fast Incremental Kernel Principal Component Analysis for Online Feature Extraction. - Seiichi Ozawa; Yohei Takeuchi; Shigeo Abe (PRICAI, 2010)

Subspace-Based L2 Support Vector Machines. - Takuya Kitamura; Shigeo Abe (Aust. J. Intell. Inf. Process. Syst., 2010)

Fast Variable Selection by Block Addition and Block Deletion. - Takashi Nagatani; Seiichi Ozawa; Shigeo Abe (J. Intell. Learn. Syst. Appl., 2010)

Support Vector Machines for Pattern Classification. - Shigeo Abe (Springer, 2010)

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

Multiple Nonlinear Subspace Methods Using Subspace-based Support Vector Machines. - Takuya Kitamura; Shigeo Abe; Yusuke Tanaka 002 (ICMLA (1), 2011)

Mining interlacing manifolds in high dimensional spaces. - Tao Ban; Changshui Zhang; Shigeo Abe; Takeshi Takahashi 001; Youki Kadobayashi (SAC, 2011)

Feature Selection by Block Addition and Block Deletion. - Takashi Nagatani; Shigeo Abe (ANNPR, 2012)

Training Mahalanobis Kernels by Linear Programming. - Shigeo Abe (ICANN (2), 2012)

Feature Selection by Iterative Block Addition and Block Deletion. - Shigeo Abe (SMC, 2013)

Incremental Feature Selection by Block Addition and Block Deletion Using Least Squares SVRs. - Shigeo Abe (ANNPR, 2014)

Incremental Input Variable Selection by Block Addition and Block Deletion. - Shigeo Abe (ICANN, 2014)

Optimizing working sets for training support vector regressors by Newton's method. - Shigeo Abe (IJCNN, 2015)

Fuzzy support vector machines for multilabel classification. - Shigeo Abe (Pattern Recognit., 2015)

Improving Generalization Abilities of Maximal Average Margin Classifiers. - Shigeo Abe (ANNPR, 2016)

Fusing sequential minimal optimization and Newton's method for support vector training. - Shigeo Abe (Int. J. Mach. Learn. Cybern., 2016)

Unconstrained large margin distribution machines. - Shigeo Abe (Pattern Recognit. Lett., 2017)

Effect of Equality Constraints to Unconstrained Large Margin Distribution Machines. - Shigeo Abe (ANNPR, 2018)

Are twin hyperplanes necessary? - Shigeo Abe (Pattern Recognit. Lett., 2018)

Analyzing Minimal Complexity Machines. - Shigeo Abe (IJCNN, 2019)

Minimal Complexity Support Vector Machines. - Shigeo Abe (ANNPR, 2020)

Minimal Complexity Support Vector Machines for Pattern Classification. - Shigeo Abe (Comput., 2020)

Soft Upper-bound Minimal Complexity LP SVMs. - Shigeo Abe (IJCNN, 2021)

Do Minimal Complexity Least Squares Support Vector Machines Work? - Shigeo Abe (ANNPR, 2022)

Soft Upper-bound Support Vector Machines. - Shigeo Abe (IJCNN, 2022)

Training Minimal Complexity Support Vector Machines with Multiple Kernels. - Shigeo Abe (SMC, 2023)

Evaluating Support Vector Machines with Multiple Kernels by Random Search. - Shigeo Abe (ANNPR, 2024)

Are Bounded Support Vectors Harmful to Stable Classification. - Shigeo Abe (IJCNN, 2024)