Shigeo Abe - RankMe

127 papers A* 1B 42C 2Misc 3Journal 36Unranked 41

Year	Rank	Type	Title / Venue / Authors
2025	B	`conf`	Accelerating Grid Search by Pruning. IJCNN Shigeo Abe
2024	B	`conf`	Are Bounded Support Vectors Harmful to Stable Classification. IJCNN Shigeo Abe
2024	—	`conf`	Evaluating Support Vector Machines with Multiple Kernels by Random Search. ANNPR Shigeo Abe
2023	B	`conf`	Training Minimal Complexity Support Vector Machines with Multiple Kernels. SMC Shigeo Abe
2022	—	`conf`	Do Minimal Complexity Least Squares Support Vector Machines Work? ANNPR Shigeo Abe
2022	B	`conf`	Soft Upper-bound Support Vector Machines. IJCNN Shigeo Abe
2021	B	`conf`	Soft Upper-bound Minimal Complexity LP SVMs. IJCNN Shigeo Abe
2020	J	`jnl`	Minimal Complexity Support Vector Machines for Pattern Classification. Comput. Shigeo Abe
2020	—	`conf`	Minimal Complexity Support Vector Machines. ANNPR Shigeo Abe
2019	B	`conf`	Analyzing Minimal Complexity Machines. IJCNN Shigeo Abe
2018	J	`jnl`	Are twin hyperplanes necessary? Pattern Recognit. Lett. Shigeo Abe
2018	—	`conf`	Effect of Equality Constraints to Unconstrained Large Margin Distribution Machines. ANNPR Shigeo Abe
2017	J	`jnl`	Unconstrained large margin distribution machines. Pattern Recognit. Lett. Shigeo Abe
2016	J	`jnl`	Fusing sequential minimal optimization and Newton's method for support vector training. Int. J. Mach. Learn. Cybern. Shigeo Abe
2016	—	`conf`	Improving Generalization Abilities of Maximal Average Margin Classifiers. ANNPR Shigeo Abe
2015	J	`jnl`	Fuzzy support vector machines for multilabel classification. Pattern Recognit. Shigeo Abe
2015	B	`conf`	Optimizing working sets for training support vector regressors by Newton's method. IJCNN Shigeo Abe
2014	—	`conf`	Incremental Feature Selection by Block Addition and Block Deletion Using Least Squares SVRs. ANNPR Shigeo Abe
2014	C	`conf`	Incremental Input Variable Selection by Block Addition and Block Deletion. ICANN Shigeo Abe
2013	B	`conf`	Feature Selection by Iterative Block Addition and Block Deletion. SMC Shigeo Abe
2012	—	`conf`	Feature Selection by Block Addition and Block Deletion. ANNPR Takashi Nagatani, Shigeo Abe
2012	—	`conf`	Training Mahalanobis Kernels by Linear Programming. ICANN (2) Shigeo Abe
2011	—	`conf`	Fast Support Vector Training by Newton's Method. ICANN (2) Shigeo Abe
2011	Misc	`conf`	Mining interlacing manifolds in high dimensional spaces. SAC Tao Ban, Changshui Zhang, Shigeo Abe, Takeshi Takahashi, Youki Kadobayashi
2011	—	`conf`	Multiple Nonlinear Subspace Methods Using Subspace-based Support Vector Machines. ICMLA (1) Takuya Kitamura, Shigeo Abe, Yusuke Tanaka
2010	B	`conf`	A Fast Incremental Kernel Principal Component Analysis for Online Feature Extraction. PRICAI Seiichi Ozawa, Yohei Takeuchi, Shigeo Abe
2010	B	`conf`	Active set training of support vector regressors. ESANN Shigeo Abe
2010	—	`conf`	Convergence Improvement of Active Set Training for Support Vector Regressors. ICANN (2) Shigeo Abe, Ryousuke Yabuwaki
2010	B	`conf`	Convergence improvement of active set support vector training. IJCNN Ryousuke Yabuwaki, Shigeo Abe
2010	—	`conf`	Evaluation of Feature Selection by Multiclass Kernel Discriminant Analysis. ANNPR Tsuneyoshi Ishii, Shigeo Abe
2010	J	`jnl`	Fast Variable Selection by Block Addition and Block Deletion. J. Intell. Learn. Syst. Appl. Takashi Nagatani, Seiichi Ozawa, Shigeo Abe
2010	—	`conf`	Feature Extraction Using Support Vector Machines. ICONIP (2) Yasuyuki Tajiri, Ryousuke Yabuwaki, Takuya Kitamura, Shigeo Abe
2010	B	`conf`	Feature selection and fast training of subspace based support vector machines. IJCNN Takuya Kitamura, Syogo Takeuchi, Shigeo Abe
2010	J	`jnl`	Subspace-Based L2 Support Vector Machines. Aust. J. Intell. Inf. Process. Syst. Takuya Kitamura, Shigeo Abe
2010	—	`book`	Support Vector Machines for Pattern Classification. Shigeo Abe
2009	J	`jnl`	A new approach to discover interlacing data structures in high-dimensional space. J. Intell. Inf. Syst. Tao Ban, Changshui Zhang, Shigeo Abe
2009	J	`jnl`	Decomposition techniques for training linear programming support vector machines. Neurocomputing Yusuke Torii, Shigeo Abe
2009	—	`conf`	Is Primal Better Than Dual. ICANN (1) Shigeo Abe
2009	B	`conf`	Sparse kernel feature analysis using FastMap and its variants. IJCNN Tao Ban, Youki Kadobayashi, Shigeo Abe
2009	B	`conf`	Sparse support vector machines by kernel discriminant analysis. ESANN Kazuki Iwamura, Shigeo Abe
2009	B	`conf`	Sparse support vector regressors based on forward basis selection. IJCNN Shigenori Muraoka, Shigeo Abe
2009	B	`conf`	Subspace based least squares support vector machines for pattern classification. IJCNN Takuya Kitamura, Shigeo Abe, Kazuhiro Fukui
2009	B	`conf`	Subspace based linear programming support vector machines. IJCNN Syogo Takeuchi, Takuya Kitamura, Shigeo Abe, Kazuhiro Fukui
2009	J	`jnl`	Subspace-based support vector machines for pattern classification. Neural Networks Takuya Kitamura, Syogo Takeuchi, Shigeo Abe, Kazuhiro Fukui
2009	J	`jnl`	Tuning membership functions of kernel fuzzy classifiers by maximizing margins. Memetic Comput. Kazuya Morikawa, Seiichi Ozawa, Shigeo Abe
2008	—	`conf`	Batch Support Vector Training Based on Exact Incremental Training. ICANN (1) Shigeo Abe
2008	B	`conf`	Comparison of sparse least squares support vector regressors trained in primal and dual. ESANN Shigeo Abe
2008	B	`conf`	Feature selection based on kernel discriminant analysis for multi-class problems. IJCNN Tsuneyoshi Ishii, Shigeo Abe
2008	—	`conf`	Improved Parameter Tuning Algorithms for Fuzzy Classifiers. ICONIP (1) Kazuya Morikawa, Shigeo Abe
2008	J	`jnl`	Kernel discriminant analysis based feature selection. Neurocomputing Tsuneyoshi Ishii, Masamichi Ashihara, Shigeo Abe
2008	—	`conf`	Sparse Least Squares Support Vector Machines by Forward Selection Based on Linear Discriminant Analysis. ANNPR Shigeo Abe
2008	B	`conf`	Sparse support vector machines trained in the reduced empirical feature space. IJCNN Kazuki Iwamura, Shigeo Abe
2007	J	`jnl`	A Learning Algorithm of Boosting Kernel Discriminant Analysis for Pattern Recognition. IEICE Trans. Inf. Syst. Shinji Kita, Seiichi Ozawa, Satoshi Maekawa, Shigeo Abe
2007	B	`conf`	An Efficient Incremental Kernel Principal Component Analysis for Online Feature Selection. IJCNN Yohei Takeuchi, Seiichi Ozawa, Shigeo Abe
2007	B	`conf`	Backward Varilable Selection of Support Vector Regressors by Block Deletion. IJCNN Takashi Nagatani, Shigeo Abe
2007	—	`conf`	Fuzzy Classifiers Based on Kernel Discriminant Analysis. ICANN (2) Ryota Hosokawa, Shigeo Abe
2007	B	`conf`	Optimizing kernel parameters by second-order methods. ESANN Shigeo Abe
2007	—	`conf`	Sparse Least Squares Support Vector Regressors Trained in the Reduced Empirical Feature Space. ICANN (2) Shigeo Abe, Kenta Onishi
2007	J	`jnl`	Sparse least squares support vector training in the reduced empirical feature space. Pattern Anal. Appl. Shigeo Abe
2006	B	`conf`	An Incremental Learning Algorithm of Ensemble Classifier Systems. IJCNN Takuya Kidera, Seiichi Ozawa, Shigeo Abe
2006	—	`conf`	Fast Training of Linear Programming Support Vector Machines Using Decomposition Techniques. ANNPR Yusuke Torii, Shigeo Abe
2006	—	`conf`	Feature Selection Based on Kernel Discriminant Analysis. ICANN (2) Masamichi Ashihara, Shigeo Abe
2006	B	`conf`	Implementing Multi-class Classifiers by One-class Classification Methods. IJCNN Tao Ban, Shigeo Abe
2006	—	`conf`	Incremental Training of Support Vector Machines Using Truncated Hypercones. ANNPR Shinya Katagiri, Shigeo Abe
2006	J	`jnl`	Incremental training of support vector machines using hyperspheres. Pattern Recognit. Lett. Shinya Katagiri, Shigeo Abe
2006	—	`conf`	Support Vector Regression Using Mahalanobis Kernels. ANNPR Yuya Kamada, Shigeo Abe
2005	J	`jnl`	Comparison between error correcting output codes and fuzzy support vector machines. Pattern Recognit. Lett. Tomonori Kikuchi, Shigeo Abe
2005	—	`conf`	Detection of Cell Forms in Multicellular Objects. CIMCA/IAWTIC Kohei Asano, Motohide Yoshimura, Shigeo Abe
2005	—	`conf`	Detection of Protein Crystallizations under Dynamic Environment. CIMCA/IAWTIC Takashi Iwai, Motohide Yoshimura, Shigeo Abe
2005	—	`conf`	Image Query by Multiresolution Spectral Histograms. CIMCA/IAWTIC Noriaki Kawamura, Motohide Yoshimura, Shigeo Abe
2005	—	`conf`	Incremental Kernel PCA for Online Learning of Feature Space. CIMCA/IAWTIC Shosuke Kimura, Seiichi Ozawa, Shigeo Abe
2005	B	`conf`	Incremental learning for online face recognition. IJCNN Seiichi Ozawa, Soon Lee Toh, Shigeo Abe, Shaoning Pang, Nikola K. Kasabov
2005	J	`jnl`	Incremental learning of feature space and classifier for face recognition. Neural Networks Seiichi Ozawa, Soon Lee Toh, Shigeo Abe, Shaoning Pang, Nikola K. Kasabov
2005	B	`conf`	Modified backward feature selection by cross validation. ESANN Shigeo Abe
2005	B	`conf`	SVM ensembles for selecting the relevant feature subsets. IJCNN Tao Ban, Shigeo Abe
2005	B	`conf`	Selecting Support Vector Candidates for Incremental Training. SMC Shinya Katagiri, Shigeo Abe
2005	—	`book`	Support Vector Machines for Pattern Classification. Shigeo Abe
2005	—	`conf`	Training of Support Vector Machines with Mahalanobis Kernels. ICANN (2) Shigeo Abe
2004	B	`conf`	Fuzzy LP-SVMs for Multiclass Problems. ESANN Shigeo Abe
2004	J	`jnl`	KPCA-based training of a kernel fuzzy classifier with ellipsoidal regions. Int. J. Approx. Reason. Kenichi Kaieda, Shigeo Abe
2004	B	`conf`	Spatially chunking support vector clustering algorithm. IJCNN Tao Ban, Shigeo Abe
2004	B	`conf`	Why pairwise is better than one-against-all or all-at-once. IJCNN Daisuke Tsujinishi, Yoshiaki Koshiba, Shigeo Abe
2003	B	`conf`	A fast incremental learning algorithm of RBF networks with long-term memory. IJCNN Keisuke Okamoto, Seiichi Ozawa, Shigeo Abe
2003	B	`conf`	A kernel fuzzy classifier with ellipsoidal regions. IJCNN Kenichi Kaieda, Shigeo Abe
2003	B	`conf`	Comparison of L1 and L2 support vector machines. IJCNN Yoshiaki Koshiba, Shigeo Abe
2003	J	`jnl`	Fuzzy least squares support vector machines for multiclass problems. Neural Networks Daisuke Tsujinishi, Shigeo Abe
2003	B	`conf`	Fuzzy least squares support vector machines. IJCNN Daisuke Tsujinishi, Shigeo Abe
2002	Misc	`conf`	Advanced Image Retrieval Using Multi-resolution Image Content. MVA Motohide Yoshimura, Hajime Kiyose, Shigeo Abe
2002	—	`conf`	Analysis of support vector machines. NNSP Shigeo Abe
2002	B	`conf`	Fuzzy support vector machines for multiclass problems. ESANN Shigeo Abe, Takuya Inoue
2001	C	`conf`	Fast Training of Support Vector Machines by Extracting Boundary Data. ICANN Shigeo Abe, Takuya Inoue
2001	B	`conf`	Generalization Improvement of a Fuzzy Classifier With Ellipsodial Regions. FUZZ-IEEE Shigeo Abe, Keita Sakaguchi
2000	—	`conf`	Fast Feature Selection by Analyzing Class Regions Approximated by Ellipsoids. IJCNN (3) Kota Kawaratani, Shigeo Abe
2000	B	`conf`	Generalization Improvement of a Fuzzy Classifier with Pyramidal Membership Functions. ICPR Shigeo Abe
2000	—	`conf`	Robust Function Approximation Using Fuzzy Rules with Ellipsoidal Regions. IJCNN (6) Hiroyasu Kubota, Hisashi Tamaki, Shigeo Abe
2000	—	`conf`	Training Three-Layer Neural Network Classifiers by Solving Inequalities. IJCNN (3) Naoki Tsuchiya, Seiichi Ozawa, Shigeo Abe
1999	J	`jnl`	A fuzzy classifier with ellipsoidal regions for diagnosis problems. IEEE Trans. Syst. Man Cybern. Part C Shigeo Abe, Ruck Thawonmas, Masahiro Kayama
1999	B	`conf`	A genetic algorithm approach to multi-objective scheduling problems with earliness and tardiness penalties. CEC Hisashi Tamaki, Etsuo Nishino, Shigeo Abe
1999	J	`jnl`	Function approximation based on fuzzy rules extracted from partitioned numerical data. IEEE Trans. Syst. Man Cybern. Part B Ruck Thawonmas, Shigeo Abe
1999	J	`jnl`	Fuzzy function approximators with ellipsoidal regions. IEEE Trans. Syst. Man Cybern. Part B Shigeo Abe
1998	J	`jnl`	Dynamic cluster generation for a fuzzy classifier with ellipsoidal regions. IEEE Trans. Syst. Man Cybern. Part B Shigeo Abe
1998	J	`jnl`	Feature selection by analyzing class regions approximated by ellipsoids. IEEE Trans. Syst. Man Cybern. Part C Shigeo Abe, Ruck Thawonmas, Yoshiki Kobayashi
1998	—	`conf`	Rule acquisition based on hyperbox representation and its applications. KES (1) Ruck Thawonmas, Shigeo Abe
1998	—	`conf`	Training of a fuzzy classifier with ellipsoidal regions by dynamic cluster generation. KES (1) Shigeo Abe
1997	J	`jnl`	A fuzzy classifier with ellipsoidal regions. IEEE Trans. Fuzzy Syst. Shigeo Abe, Ruck Thawonmas
1997	J	`jnl`	A novel approach to feature selection based on analysis of class regions. IEEE Trans. Syst. Man Cybern. Part B Ruck Thawonmas, Shigeo Abe
1997	—	`conf`	Function Approximation with Partitioned Ellipsoidal Regions. ICONIP (1) Ruck Thawonmas, Shigeo Abe
1996	—	`conf`	A fuzzy classifier based on partitioned hyperboxes. ICNN Ruck Thawonmas, Shigeo Abe
1996	J	`jnl`	Convergence acceleration of the Hopfield neural network by optimizing integration step sizes. IEEE Trans. Syst. Man Cybern. Part B Shigeo Abe
1996	J	`jnl`	Extraction of Fuzzy Rules for Classification Based on Partitioned Hyperboxes. J. Intell. Fuzzy Syst. Ruck Thawonmas, Shigeo Abe
1996	J	`jnl`	LSI module placement using the kohonen network. Syst. Comput. Jpn. Takeshi Inoue, Shigeo Abe, Masahiro Kayama
1996	J	`jnl`	Tuning of a fuzzy classifier derived from data. Int. J. Approx. Reason. Shigeo Abe, Ming-Shong Lan, Ruck Thawonmas
1995	J	`jnl`	A method for fuzzy rules extraction directly from numerical data and its application to pattern classification. IEEE Trans. Fuzzy Syst. Shigeo Abe, Ming-Shong Lan
1995	J	`jnl`	A neural-network-based fuzzy classifier. IEEE Trans. Syst. Man Cybern. Volkmar Uebele, Shigeo Abe, Ming-Shong Lan
1995	—	`conf`	Feature reduction based on analysis of fuzzy regions. ICNN Ruck Thawonmas, Shigeo Abe
1995	—	`conf`	Fuzzy Systems with Learning Capability. Fuzzy Logic in Artificial Intelligence Shigeo Abe
1995	J	`jnl`	Fuzzy rules extraction directly from numerical data for function approximation. IEEE Trans. Syst. Man Cybern. Shigeo Abe, Ming-Shong Lan
1994	J	`jnl`	Training neural net classifier to improve generalization capability. Syst. Comput. Jpn. Masahiro Kayama, Shigeo Abe
1993	J	`jnl`	Extracting algorithms from pattern classification neural networks. Neural Networks Shigeo Abe, Masahiro Kayama, Hiroshi Takenaga, Tadaaki Kitamura
1992	J	`jnl`	Solving inequality constrained combinatorial optimization problems by the hopfield neural networks. Neural Networks Shigeo Abe, Junzo Kawakami, Kotaro Hirasawa
1990	B	`conf`	Convergence of the Hopfield neural networks with inequality constraints. IJCNN Shigeo Abe
1990	B	`conf`	Learning by parallel forward propagation. IJCNN Shigeo Abe
1990	Misc	`conf`	Optimal Input Selection of Neural Networks by Sensitivity Analysis and Its Application to Image Recognition. MVA Hiroshi Takenaga, Shigeo Abe, Masao Takatoo, Masahiro Kayama, Tadaaki Kitamura, Yosiyuki Okuyama
1988	—	`conf`	Instruction Architecture for a High Performance Integrated Prolog Processor IPP. ICLP/SLP Ken-ichi Kurosawa, S. Yamaguchi, Shigeo Abe, Tadaaki Bandoh
1987	A*	`conf`	High Performance Integrated Prolog Processor IPP. ISCA Shigeo Abe, Tadaaki Bandoh, S. Yamaguchi, Ken-ichi Kurosawa, Kaori Kiriyama
1986	—	`conf`	A New Optimization Technique for a Prolog Computer. COMPCON Shigeo Abe, Ken-ichi Kurosawa, Kaori Kiriyama
1982	—	`conf`	Preliminary Performance Evaluation of Data Flow Computers. COMPCON Shigeo Abe, Ryosei Hiraoka, Yasushi Fukunaga, Tadaaki Bandoh, Kotaro Hirasawa, Yukio Kawamoto