Journal Papers

  1. T. Nagatani, S. Ozawa, and S. Abe, Fast Variable Selection by Block Addition and Block Deletion, Journal of Intelligent Learning Systems and Applications, Vol. 2, No.4, pp. 200-211, 2010.

  2. T. Kitamura, S. Takeuchi, and S. Abe, Empirical Subspace Based Support Vector Machines, Transactions on Mathematical Modeling and Its Applications, Vol. 3, No. 3, pp. 12-23, 2010 (in Japanese).

  3. K. Morikawa, S. Ozawa, and S. Abe, Tuning Membership Functions of Kernel Fuzzy Classifiers by Maximizing Margins, Memetic Computing, Vol. 1, No. 3, pp. 221-228, 2009.

  4. T. Kitamura, S. Takeuchi, S. Abe and K. Fukui, Subspace-Based Support Vector Machines for Pattern Classification, Neural Networks, Vol. 22, Nos. 5-6, pp. 558-567, 2009.

  5. Y. Torii and S. Abe, Decomposition Techniques for Training Linear Programming Support Vector Machines, Neurocomputing, Vol. 72, Nos. 4-6, pp. 973-984, 2009.

  6. T. Ishii, M. Ashihara, and S. Abe, Kernel Discriminant Analysis Based Feature Selection, Neurocomputing, Vol. 71, pp. 2544-2552, 2008.

  7. S. Kita, S. Ozawa, S. Maekawa, and S. Abe, A Learning Algorithm of Boosting Kernel Discriminant Analysis for Pattern Recognition, IEICE Trans. Information Systems, Vol. E90-D, No. 11, pp. 1853-1863, 2007.

  8. S. Abe, Sparse Least Squares Support Vector Training in the Reduced Empirical Feature Space, Pattern Analysis & Applications, Vol. 10, No. 3, pp. 203-214, 2007.

  9. S. Katagiri and S. Abe, Incremental Training of Support Vector Machines Using Hyperspheres, Pattern Recognition Letters, Vol. 27, No. 13, pp. 1495-1507, 2006. (abstract).

  10. S. Ozawa, S. L. Toh, S. Abe, S. Pang, and N. Kasabov, Incremental Learning of Feature Space and Classifier for Face Recognition, Neural Networks,Vol. 18, Nos. 5, 6, pp. 575-584, 2005 (abstract).

  11. T. Kikuchi and S. Abe, Comparison between Error Correcting Output Codes and Fuzzy Support Vector Machines, Pattern Recognition Letters, Vol. 26, No. 12, pp. 1937-1945, 2005. (abstract).

  12. K. Okamoto, S. Ozawa, and S. Abe, A Fast Incremental Learning Algorithm of Radial Basis Function Networks, Trans. SICE, Vol. 40, No. 12, pp. 1227-1235, 2004 (in Japanese).

  13. Y. Hirokawa and S. Abe, Steepest Ascent Training of Support Vector Regressors, IEEJ Trans. EIS, Vol. 124-C, No. 10, 2004 (in Japanese). (pdf)

  14. K. Kaieda and S. Abe, KPCA-Based Training of a Kernel Fuzzy Classifier with Ellipsoidal Regions, International Journal of Approximate Reasoning, Vol. 37, No. 3, pp. 189-217, 2004. (abstract)

  15. F. Takahashi and S. Abe, Optimal Structure of Decision-Tree-Based Pairwise Support Vector Machines, Trans. Institute of Systems, Control and Information Engineers, Vol. 17, No. 3, pp. 122-130, 2004 (in Japanese).

  16. D. Tsujinishi and S. Abe, Fuzzy Least Squares Support Vector Machines for Multiclass Problems, Neural Networks, Vol. 16, Nos. 5-6, pp. 785-792, 2003. (abstract)

  17. T. Nishikawa and S. Abe, Maximum Margin Multilayer Neural Networks, Trans. Institute of Systems, Control and Information Engineers, Vol. 16, No. 8, pp. 421-428, 2003 (in Japanese).

  18. F. Takahashi and S. Abe, Decision-Tree-Based Support Vector Machines, Trans. Institute of Systems, Control and Information Engineers, Vol. 16, No. 3, pp. 125-132, 2003 (in Japanese).

  19. T. Inoue and S. Abe, Improvement of Generalization Ability of Multiclass Support Vector Machines by Introducing Fuzzy Logic and Bayes Theory, Trans. Institute of Systems, Control and Information Engineers, Vol. 15, No. 12, pp. 643-651, 2002 (in Japanese).

  20. T. Takigawa and S. Abe, High Speed Training of a Fuzzy Classifier with Polyhedral Regions, Trans. Institute of Systems, Control and Information  Engineers,  Vol. 15, No. 12, 2002 (in Japanese).

  21. S. Abe, Y. Hirokawa, and S. Ozawa，Training of Support Vector Machines by the Steepest Ascent Method, Trans. Institute of Systems, Control and Information Engineers,  Vol. 15, No. 11, 2002 (in Japanese).

  22. T. Inoue and S. Abe, Architecture of Fuzzy Support Vector Machines for Pattern Classification, Trans. Institute of Systems, Control and Information Engineers,   Vol. 15, No. 2, pp. 99-105, 2002 (in Japanese).

  23. S. Abe and K. Sakaguchi, Improvement of Generalization Ability of a Fuzzy Classifier
    with Ellipsoidal Regions by Maximizing Margins, Trans. Institute of Systems, Control and Information Engineers,  Vol. 15, No. 2, pp. 92-98, 2002 (in Japanese).

  24. T. Inoue, T. Ueoka, H. Tamaki, and S. Abe, Fast Training of Support Vector Machines and Performance Comparison with Fuzzy Classifiers, Trans. Institute of Systems, Control and Information Engineers, Vol. 15, No. 1, pp. 25-33, 2002 (in Japanese).

  25. H. Kubota and S. Abe, Robust Function Approximation Using Ellipsoidal Fuzzy Rules, Trans. Institute of Systems, Control and Information Engineers,  Vol. 14, No. 7, pp. 373-379, 2001 (in Japanese).

  26. T. Shimozaki, T. Takigawa, and S. Abe, A Fuzzy Classifier with Polyhedral Regions, Trans. Institute of Systems, Control and Information Engineers, Vol. 14, No. 7, pp. 365-372, 2001 (in Japanese).

  27. J. Park, S. Ozawa, and S. Abe, Performance Improvement of Dynamical Associative Memories by Solving Linear Ineuqlities, Trans. IEE of Japan, Vol. 121-C, No. 5, pp. 899-905, May 2001 (in Japanese).

  28. K. Kawaratani and S. Abe，Fast Forward Feature Selection by Analyzing Class Regions Approximated by Ellipsoids, Trans. Institute of Systems, Control and Information Engineers, Vol. 14, No. 5, 2001 (in Japanese).

  29. T. Eguchi, H. Tamaki, and S. Abe，A Robust Fuzzy Classifier with Ellipsoidal Regions，Trans. Institute of Systems, Control and Information Engineers, Vol.  13, No. 9, 433-440, 2000 (in Japanese).

  30. S. Abe and R. Thawonmas，Improvement of Generalization Ability of a Fuzzy Classifier with Hyperbox Regions by Quadratic Membership Functions, Trans. Institute of Systems, Control and Information Engineers, Vol. 13, No. 8, 377-376, 2000 (in Japanese).

  31. N. Tsuchiya,  S. Ozawa, and S. Abe, Fast Training of Three-Layered Neural Network Classifiers by Solving Inequalities，Trans. Institute of Systems, Control and Information Engineers，Vol. 13，No. 6, pp. 276-283, 2000 (in Japanese).

  32. M. Kobayashi, M. Kimata, and S. Abe，Improvement of Generalization Ability of a Fuzzy Classifier with Ellipsoidal Regions by the Optimum Division of Data，Trans. Institute of Systems, Control and Information Engineers，Vol. 13，No. 2，pp.  87-94, 2000 (in Japanese).

  33. M. Shimizu and S. Abe，On Input Invariance of Fuzzy Classifiers with Learning Capability，Trans. Institute of Systems, Control and Information Engineers，Vol. 12，No. 12，1999 (in Japanese).

  34. T. Eguchi and S. Abe，High Speed Training of a Fuzzy Classifier with Ellipsoidal Regions, Trans. Institute of Systems, Control and Information Engineers， Vol. 12，No. 9，pp. 558-565, 1999 (in Japanese).

  35. H. Tamaki, E. Nishino, and S. Abe, Modeling and Genetic Solution for Scheduling Problems wtih Regular and Non-Regulra Objective Functions, Trans. SICE, Vol. 35, No.  5, pp. 662-667, 1999 (in Japanese).

  36. H. Tamaki, T. Arai, and S. Abe, A Genetic Algorithm Approach to Optimization Problems with Uncertainties, Trans. Institute of Systems, Control and Information Engineers，Vol. 12, No. 5, pp. 297-303, May 1999 (in Japanese).

  37. S. Abe, Fuzzy Function Approximators with Ellipsoidal Regions, IEEE Trans. Systems, Man, and Cybernetics-Part B, Vol. 29, No. 5, pp. 654-661, October 1999.

  38. R. Thawonmas and S. Abe, Function Approximation Based on Fuzzy Rules Extracted from Partitioned Numerical Data, IEEE Trans. Systems, Man, and Cybernetics-Part B, Vol. 29, No. 4, pp. 525-534, August 1999.

  39. S. Abe, R. Thawonmas, and M. Kayama, A Fuzzy Classifier with Ellipsoidal Regions for Diagnosis Problems, IEEE Trans. Systems, Man, and Cybernetics -Part C, Vol. 29, No. 1, pp. 140-149, Jan. 1999.

  40. S. Abe, Dynamic Cluster Generation for a Fuzzy Classifier with Ellipsoidal Regions, IEEE Trans. Systems, Man, and Cybernetics-Part B, Vol. 28, No. 6, pp. 869-876, Dec. 1998.

  41. R. Thawonmas and S. Abe, Tuning of a Fuzzy Classifier Derived from Data by Solving Inequalities, Trans. Institute of Electronics, Information and Communication Engineers of Japan, Vol. E81-D, No. 2, pp. 224-235, February 1998.

  42. S. Abe, R. Thawonmas, and Y. Kobayashi, Feature Selection by Analyzing Class Regions Approximated by Ellipsoids, IEEE Trans. Systems, Man, and Cybernetics-Part C, Vol. 28, No. 2, pp. 282-287, May 1998.

  43. S. Abe and R. Thawonmas, A Fuzzy Classifier with Ellipsoidal Regions, IEEE Trans. Fuzzy Systems, Vol. 5, No. 3,  pp. 358-368, August 1997.

  44. R. Thawonmas and S. Abe, A Novel Approach to Feature Selection Based on Analysis of Fuzzy Regions, IEEE Trans. Systems, Man, and Cybernetics-Part  B, Vol. 27, No. 2, pp. 196-207, April 1997.

  45. R. Thawonmas and S. Abe, Extraction of Fuzzy Rules for Classification Based on Partitioned Hyperboxes, The Journal of Intelligent and Fuzzy Systems, Vol. 4, No. 3, pp. 215-226, 1996.

  46. J. Mitchell and S. Abe, Fuzzy Clustering Networks: Design Criteria for Approximation and Prediction, Trans. Institute of Electronics, Information and Communication Engineers of Japan, Vol. E79-D, No. 1, pp. 63-71, January 1996.

  47. S. Abe, M.-S. Lan, and R. Thawonmas, Tuning of a Fuzzy Classifier Derived from Data, The International Journal of Approximate Reasoning,  Vol. 14, No. 1, pp. 1-24, January l996.

  48. S. Abe, Convergence Acceleration of the Hopfield Neural Network by Optimizing Integration Step Sizes, IEEE Trans. Systems, Man, and Cybernetics-Part B, Vol. 26, No. 1, pp. 194-201, February 1996.

  49. T. Inoue, S. Abe, and M. Kayama, LSI Module Plcacement Method Using Kohonen's Feature Maps，Trans. IEICE, Vol. J78-D-II, No. 3, pp. 520-531, March 1995 (in Japanese).

  50. S. Abe, H. Date, and Y. Obuchi, LSI Module Placement Using the Hopfield Neural Network with Non-zero Diagonal Elements, IPSJ Journal，Vol. 36, No. 2, pp. 258-265, February 1995 (in Japanese).

  51. S. Abe and M.-S. Lan, A Method for Fuzzy Rules Extraction Directly from Numerical Data and Its Application to Pattern Classification, IEEE Trans. Fuzzy Systems, Vol. 3, No. 1, pp. 18-28, February 1995.

  52. F. Uebele, S. Abe, and M.-S. Lan, A Neural-Network-Based Fuzzy Classifier, IEEE Trans. System, Man, and Cybernetics, Vol. 25, No. 2, pp. 353-361, February 1995.

  53. S. Abe and M-S Lan, Fuzzy Rules Extraction Directly from Numerical Data for Function Approximation, IEEE Trans. Systems, Man, and Cybernetics, Vol. 25, No. 1, pp. 119-129, January 1995.

  54. S. Abe and A. H. Gee, Global Convergence of the Hopfield Neural Network with Non-zero Diagonal Elements, IEEE Trans. Circuits and Systems  II  (CAS-II), Vol. 42, No. 1, pp. 39-45, 1995.

  55. S. Abe, M.-S. Lan, and J. Motoike, Optimizing Composite Neural Networks for Very Hard Classification Problems, Trans. Information Processing Society of Japan, Vol. 35, No. 9, pp. 1807-1814, September 1994.

  56. S. Abe, Global Convergence and Suppression of Spurious States of the Hopfield Neural Networks, IEEE Trans. Circuits and Systems I (CAS-I), Vol. 40, No. 4, pp. 246-257, April 1993.

  57. S. Abe, M. Kayama, H. Takenaga, and T. Kitamura, Extracting Algorithms from Pattern Classification Neural Networks, Neural Networks,  Vol. 6, No. 5, pp. 729-735, 1993.

  58. M. Kayama and S. Abe, Training Neural Net Classifier for Improving Generalization Capability, Trans. IEICE, Vol. J76-DII,  No. 4, pp. 863-872, April 1993 (in Japanese).

  59. S. Abe, M. Kayama, and H. Takenaga, Acceleration of Learning and Improvemnet of Generalization Ability for Pattern Classification Networks, Trans.  IEICE, Vol. J76-DII, No. 3, pp. 647-652, 1993年 3月 (in Japanese).

  60. M. Kayama, S. Abe, H. Takenaga, and Y. Morooka, Dependency of Generalization Capability for a Multi-Layered Neural Network on its Number of Hidden Units， Trans. IEE of Japan, Vol. 113-D, No. 3, pp. 341-348, March 1993 (in Japanese).

  61. S. Abe，Determination of Weights of the Hopfield Neural Networks and Its Evaluation，IPSJ Journal，Vol. 34, No. 1, pp. 21-28, January 1993 (in Japanese).

  62. M. Kayama, S. Abe, H. Takenaga, Y. Morooka, Determining Optimal Number of Hidden Units for Mult-layered Neural Networks，Trans. IEE of Japan, Vol. 112-D, No. 11, November 1992 (in Japanese).

  63. S. Abe, J. Kawakami, and K. Hirasawa, Solving Inequality Constrained Combinatorial Optimization Problems by the Hopfield Neural Networks, Neural Networks, Vol. 5, No. 4, pp. 663-670, 1992.

  64. S. Abe, M. Kayama, and H. Takenaga, How Neural Networks for Pattern Recognition Can Be Synthesized, Journal of Information Processing,  Vol. 14, No. 3, pp. 344-350, 1991.

  65. H. Takenaga, S. Abe, M. Takatoo, M. Kayama, T. Kitamura, and Y. Okuyama, Input Layer Optimization of Neural Networks by Sensitivity Analysis and Its Apploication to Recognition of Numerals，Trans. IEE of Japan, Vol. 111-D, No. 1, pp. 36-43, January 1991 (in Japanese).

  66. S. Abe, K. Kawabata, and K. Kurosawa，Optimization of Prolog Programs， IPSJ Journal，Vol. 30, No. 5, pp. 587-595, May 1989 (in Japanese).

  67. S. Abe, K. Kiriyama and K. Kurosawa, Optimizing Techniques for a Prolog Compiler, Revue D’Intelligence Artificille, Vol. 2, No. 2, pp. 7-28, 1989.

  68. K. Kiriyama, S. Abe, K. Kurosawa， Optimized Compiler for Integrated Prolog Processor IPP and Performance Evaluation，IPSJ Journal，Vol. 29, No. 6, pp. 589-595, June 1988 (in Japanese).

  69. M. Takatoo, S. Abe, K. Hirasawa, M. Goto, T. Kato, and T. Kanke, Floating Vector Processor for Power System Simulation, IEEE Trans. Power Apparatus and Systems, Vol. PAS-104, No. 12, pp. 3361-3366, December 1985.

  70. S. Abe, M. Takatoo, T. Bandoo, K. Hirasawa, and T. Katoo，Integrated Vector Processor for Super Minicomputer, IPSJ Journal，Vol.  25, No. 4, pp. 614-621, April 1984 (in Japanese).

  71. S. Abe, A. Isono, and B. Kondo, Determination of Power System Voltage Stability, Part 3: Dynamical Approach, Trans. IEE of Japan, Vol. 103B, No. 5, pp.  349-356, May 1983

  72. S. Abe, Y. Fukunaga, A. Isono, and B. Kondo, Power System Voltage Stability, IEEE Trans. Power Apparatus and Systems, Vol. PAS-101, No. 10, pp. 3830-3840, October 1982.

  73. D.I.H. Sun, S. Abe, R.R. Shoults, M.-S. Chen, P. Eichenberger, and D. Farris, Calculations of Energy Losses in a Distributed System, IEEE Trans. Power Apparatus and Systems, Vol. PAS-99, No. 4, pp. 1347-1356, July/August 1980.

  74. S. Abe, N. Hamada, A. Isono, and K. Okuda, Load Flow Convergence in the Vicinity of a Voltage Stability Limit, IEEE Trans. Power Apparatus and Systems, Vol. PAS-97, No. 6, pp. 1983-1993, Nov/Dec 1978.

  75. S. Abe and M. Goto, Determination of Steady State Switching Sequence of Power Networks, Trans. IEE of Japan, Vol. 97B, No. 6, pp. 359-366, June 1977.

  76. S. Abe and A. Isono, Initial Value Selection of Load Flow Calculations  in the Vicinity of a Voltage Stability Limit, Trans. IEE of Japan,  Vol. 97, No. 1, pp. 23-30, January 1977.

  77. S. Abe and A. Isono, Determination of Power System Voltage Stability, Part 2: Digital Simulation, Trans. IEE of Japan, Vol. 96B, No. 4, pp. 179-186, April 1976.

  78. S. Abe and A. Isono, Determination of Power System Voltage Stability, Part 1: Theory, Trans. IEE of Japan, Vol. 96B, No. 4, pp. 171-178, April 1976.