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Mineichi Kudo: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Atsuyoshi Nakamura, Mineichi Kudo, Akira Tanaka, Kazuhiko Tanabe
    Collaborative Filtering Using Projective Restoration Operators. [Citation Graph (0, 0)][DBLP]
    Discovery Science, 2003, pp:393-401 [Conf]
  2. Ichigaku Takigawa, Mineichi Kudo, Atsuyoshi Nakamura, Jun Toyama
    On the Minimum l1-Norm Signal Recovery in Underdetermined Source Separation. [Citation Graph (0, 0)][DBLP]
    ICA, 2004, pp:193-200 [Conf]
  3. Hidehiko Ino, Mineichi Kudo, Atsuyoshi Nakamura
    A Comparative Study of Algorithms for Finding Web Communities. [Citation Graph (0, 0)][DBLP]
    ICDE Workshops, 2005, pp:1257- [Conf]
  4. Michal Haindl, Jiri Grim, Petr Somol, Pavel Pudil, Mineichi Kudo
    A Gaussian Mixture-Based Colour Texture Model. [Citation Graph (0, 0)][DBLP]
    ICPR (3), 2004, pp:177-180 [Conf]
  5. Mineichi Kudo, Hideyuki Imai, Masaru Shimbo
    A Histogram-Based Classifier on Overlapped Bins. [Citation Graph (0, 0)][DBLP]
    ICPR, 2000, pp:2029-2033 [Conf]
  6. Masafumi Yamada, Mineichi Kudo, Hidetoshi Nonaka, Jun Toyama
    Hipprint Person Identification and Behavior Analys. [Citation Graph (0, 0)][DBLP]
    ICPR (4), 2006, pp:533-536 [Conf]
  7. Naoto Abe, Mineichi Kudo
    Entropy Criterion for Classifier-Independent Feature Selection. [Citation Graph (0, 0)][DBLP]
    KES (4), 2005, pp:689-695 [Conf]
  8. Hiroyuki Hasegawa, Mineichi Kudo, Atsuyoshi Nakamura
    Empirical Study on Usefulness of Algorithm SACwRApper for Reputation Extraction from the WWW. [Citation Graph (0, 0)][DBLP]
    KES (4), 2005, pp:668-674 [Conf]
  9. Taisuke Hosokawa, Mineichi Kudo
    Person Tracking with Infrared Sensors. [Citation Graph (0, 0)][DBLP]
    KES (4), 2005, pp:682-688 [Conf]
  10. Akira Tanaka, Ichigaku Takigawa, Hideyuki Imai, Mineichi Kudo, Masaaki Miyakoshi
    Projection Learning Based Kernel Machine Design Using Series of Monotone Increasing Reproducing Kernel Hilbert Spaces. [Citation Graph (0, 0)][DBLP]
    KES, 2004, pp:1058-1064 [Conf]
  11. Hiroshi Tenmoto, Mineichi Kudo
    Finding and Auto-labeling of Task Groups on E-Mails and Documents. [Citation Graph (0, 0)][DBLP]
    KES (4), 2005, pp:696-702 [Conf]
  12. Masafumi Yamada, Mineichi Kudo
    Combination of Weak Evidences by D-S Theory for Person Recognition. [Citation Graph (0, 0)][DBLP]
    KES, 2004, pp:1065-1071 [Conf]
  13. Masafumi Yamada, Jun Toyama, Mineichi Kudo
    Person Recognition by Pressure Sensors. [Citation Graph (0, 0)][DBLP]
    KES (4), 2005, pp:703-708 [Conf]
  14. Ichigaku Takigawa, Mineichi Kudo, Atsuyoshi Nakamura
    The Convex Subclass Method: Combinatorial Classifier Based on a Family of Convex Sets. [Citation Graph (0, 0)][DBLP]
    MLDM, 2005, pp:90-99 [Conf]
  15. Atsuyoshi Nakamura, Mineichi Kudo
    Mining Frequent Trees with Node-Inclusion Constraints. [Citation Graph (0, 0)][DBLP]
    PAKDD, 2005, pp:850-860 [Conf]
  16. Atsuyoshi Nakamura, Mineichi Kudo, Akira Tanaka
    Collaborative Filtering Using Restoration Operators. [Citation Graph (0, 0)][DBLP]
    PKDD, 2003, pp:339-349 [Conf]
  17. Tetsuya Murai, Masayuki Sanada, Yasuo Kudo, Mineichi Kudo
    A Note on Ziarko's Variable Precision Rough Set Model and Nonmonotonic Reasoning. [Citation Graph (0, 0)][DBLP]
    Rough Sets and Current Trends in Computing, 2004, pp:103-108 [Conf]
  18. Mineichi Kudo, Tetsuya Murai
    A New Treatment and Viewpoint of Information Tables. [Citation Graph (0, 0)][DBLP]
    RSFDGrC (1), 2005, pp:234-243 [Conf]
  19. Yuji Muto, Mineichi Kudo
    Discernibility-Based Variable Granularity and Kansei Representations. [Citation Graph (0, 0)][DBLP]
    RSFDGrC (1), 2005, pp:692-700 [Conf]
  20. Naoto Abe, Mineichi Kudo, Masaru Shimbo
    Classifier-Independent Feature Selection Based on Non-parametric Discriminant Analysis. [Citation Graph (0, 0)][DBLP]
    SSPR/SPR, 2002, pp:470-479 [Conf]
  21. Naoto Abe, Mineichi Kudo, Jun Toyama, Masaru Shimbo
    A Divergence Criterion for Classifier-Independent Feature Selection. [Citation Graph (0, 0)][DBLP]
    SSPR/SPR, 2000, pp:668-676 [Conf]
  22. Kazuaki Aoki, Mineichi Kudo
    Decision Tree Using Class-Dependent Feature Subsets. [Citation Graph (0, 0)][DBLP]
    SSPR/SPR, 2002, pp:761-769 [Conf]
  23. Mineichi Kudo, Hideyuki Imai, Akira Tanaka, Tetsuya Murai
    A Nearest Neighbor Method Using Bisectors. [Citation Graph (0, 0)][DBLP]
    SSPR/SPR, 2004, pp:885-893 [Conf]
  24. Mineichi Kudo, Jack Sklansky
    Classifier-Independent Feature Selection For Two-Stage Feature Selection. [Citation Graph (0, 0)][DBLP]
    SSPR/SPR, 1998, pp:548-554 [Conf]
  25. Mineichi Kudo, Petr Somol, Pavel Pudil, Masaru Shimbo, Jack Sklansky
    Comparison of Classifier-Specific Feature Selection Algorithms. [Citation Graph (0, 0)][DBLP]
    SSPR/SPR, 2000, pp:677-686 [Conf]
  26. M. Sato, Mineichi Kudo, Jun Toyama, Masaru Shimbo
    Feature Selection For a Nonlinear Classifier. [Citation Graph (0, 0)][DBLP]
    SSPR/SPR, 1998, pp:555-563 [Conf]
  27. Akira Tanaka, Masashi Sugiyama, Hideyuki Imai, Mineichi Kudo, Masaaki Miyakoshi
    Model Selection Using a Class of Kernels with an Invariant Metric. [Citation Graph (0, 0)][DBLP]
    SSPR/SPR, 2006, pp:862-870 [Conf]
  28. Hiroshi Tenmoto, Mineichi Kudo, Masaru Shimbo
    Selection of the Number of Components Using a Genetic Algorithm for Mixture Model Classifiers. [Citation Graph (0, 0)][DBLP]
    SSPR/SPR, 2000, pp:511-520 [Conf]
  29. Hiroshi Tenmoto, Mineichi Kudo, Masaru Shimbo
    MDL-Based Selection of the Number of Components in Mixture Models for Pattern Classification. [Citation Graph (0, 0)][DBLP]
    SSPR/SPR, 1998, pp:831-836 [Conf]
  30. Hiroshi Tenmoto, Yasukuni Mori, Mineichi Kudo
    Classifier-Independent Visualization of Supervised Data Structures Using a Graph. [Citation Graph (0, 0)][DBLP]
    SSPR/SPR, 2004, pp:1043-1051 [Conf]
  31. Hidehiko Ino, Mineichi Kudo, Atsuyoshi Nakamura
    Partitioning of Web graphs by community topology. [Citation Graph (0, 0)][DBLP]
    WWW, 2005, pp:661-669 [Conf]
  32. Mineichi Kudo, Y. Iida, Masaru Shimbo
    Syntactic pattern analysis of 5'-splice site sequences of mRNA precursors in higher eukaryote genes. [Citation Graph (0, 0)][DBLP]
    Computer Applications in the Biosciences, 1987, v:3, n:4, pp:319-324 [Journal]
  33. Mineichi Kudo, S. Kitamura-Abe, Masaru Shimbo, Y. Lida
    Analysis of context of 5'-splice site sequences in mammalian mRNA precursors by subclass method. [Citation Graph (0, 0)][DBLP]
    Computer Applications in the Biosciences, 1992, v:8, n:4, pp:367-376 [Journal]
  34. Yuji Muto, Mineichi Kudo, Tetsuya Murai
    Reduction of Attribute Values for Kansei Representation. [Citation Graph (0, 0)][DBLP]
    JACIII, 2006, v:10, n:5, pp:666-672 [Journal]
  35. Hiroki Hayashi, Mineichi Kudo, Jun Toyama, Masaru Shimbo
    Fast Labelling of Natural Scenes Using Enhanced Knowledge. [Citation Graph (0, 0)][DBLP]
    Pattern Anal. Appl., 2001, v:4, n:1, pp:20-27 [Journal]
  36. Naoto Abe, Mineichi Kudo, Jun Toyama, Masaru Shimbo
    Classifier-independent feature selection on the basis of divergence criterion. [Citation Graph (0, 0)][DBLP]
    Pattern Anal. Appl., 2006, v:9, n:2-3, pp:127-137 [Journal]
  37. Naoto Abe, Mineichi Kudo
    Non-parametric classifier-independent feature selection. [Citation Graph (0, 0)][DBLP]
    Pattern Recognition, 2006, v:39, n:5, pp:737-746 [Journal]
  38. Mineichi Kudo, Jack Sklansky
    Comparison of algorithms that select features for pattern classifiers. [Citation Graph (0, 0)][DBLP]
    Pattern Recognition, 2000, v:33, n:1, pp:25-41 [Journal]
  39. Mineichi Kudo, Masaru Shimbo
    Efficient regular grammatical inference techniques by the use of partial similarities and their logical relationships. [Citation Graph (0, 0)][DBLP]
    Pattern Recognition, 1988, v:21, n:4, pp:401-409 [Journal]
  40. Mineichi Kudo, Masaru Shimbo
    Feature selection based on the structural indices of categories. [Citation Graph (0, 0)][DBLP]
    Pattern Recognition, 1993, v:26, n:6, pp:891-901 [Journal]
  41. Mineichi Kudo, Shinichi Yanagi, Masaru Shimbo
    Construction of class regions by a randomized algorithm: a randomized subclass method. [Citation Graph (0, 0)][DBLP]
    Pattern Recognition, 1996, v:29, n:4, pp:581-588 [Journal]
  42. Hiroshi Tenmoto, Mineichi Kudo, Masaru Shimbo
    Piecewise linear classifiers with an appropriate number of hyperplanes. [Citation Graph (0, 0)][DBLP]
    Pattern Recognition, 1998, v:31, n:11, pp:1627-1634 [Journal]
  43. Mineichi Kudo, Koji Mizukami, Yuji Nakamura, Masaru Shimbo
    Realization of membership quiries in character recognition. [Citation Graph (0, 0)][DBLP]
    Pattern Recognition Letters, 1996, v:17, n:1, pp:77-82 [Journal]
  44. Mineichi Kudo, Naoto Masuyama, Jun Toyama, Masaru Shimbo
    Simple termination conditions for k-nearest neighbor method. [Citation Graph (0, 0)][DBLP]
    Pattern Recognition Letters, 2003, v:24, n:9-10, pp:1203-1213 [Journal]
  45. Mineichi Kudo, Yoichiro Torii, Yasukuni Mori, Masaru Shimbo
    Approximation of class regions by quasi convex hulls. [Citation Graph (0, 0)][DBLP]
    Pattern Recognition Letters, 1998, v:19, n:9, pp:777-786 [Journal]
  46. Mineichi Kudo, Jun Toyama, Masaru Shimbo
    Multidimensional curve classification using passing-through regions. [Citation Graph (0, 0)][DBLP]
    Pattern Recognition Letters, 1999, v:20, n:11-13, pp:1103-1111 [Journal]
  47. Kazuaki Aoki, Toshiharu Watanabe, Mineichi Kudo
    Design of decision trees using class-dependent feature subsets. [Citation Graph (0, 0)][DBLP]
    Systems and Computers in Japan, 2005, v:36, n:4, pp:37-47 [Journal]
  48. Yoshinori Yanagihara, Masanori Kawakami, Mineichi Kudo, Jun Toyama, Masaru Shimbo
    A two-channel coding of images using spline surfaces. [Citation Graph (0, 0)][DBLP]
    Systems and Computers in Japan, 2001, v:32, n:6, pp:13-20 [Journal]
  49. Hisashi Tosaka, Atsuyoshi Nakamura, Mineichi Kudo
    Mining Subtrees with Frequent Occurrence of Similar Subtrees. [Citation Graph (0, 0)][DBLP]
    Discovery Science, 2007, pp:286-290 [Conf]
  50. Mineichi Kudo, Satoshi Shirai, Hiroshi Tenmoto
    A Combination of Sample Subsets and Feature Subsets in One-Against-Other Classifiers. [Citation Graph (0, 0)][DBLP]
    MCS, 2007, pp:241-250 [Conf]
  51. Yohji Shidara, Atsuyoshi Nakamura, Mineichi Kudo
    CCIC: Consistent Common Itemsets Classifier. [Citation Graph (0, 0)][DBLP]
    MLDM, 2007, pp:490-498 [Conf]
  52. Yuji Muto, Mineichi Kudo, Yohji Shidara
    Reduction of Categorical and Numerical Attribute Values for Understandability of Data and Rules. [Citation Graph (0, 0)][DBLP]
    RSKT, 2007, pp:211-218 [Conf]
  53. Akira Tanaka, Hideyuki Imai, Mineichi Kudo, Masaaki Miyakoshi
    Integrated kernels and their properties. [Citation Graph (0, 0)][DBLP]
    Pattern Recognition, 2007, v:40, n:11, pp:2930-2938 [Journal]

  54. Algorithms for Adversarial Bandit Problems with Multiple Plays. [Citation Graph (, )][DBLP]


  55. Classifier Selection in a Family of Polyhedron Classifiers. [Citation Graph (, )][DBLP]


  56. What Sperner Family Concept Class is Easy to Be Enumerated? [Citation Graph (, )][DBLP]


  57. Classification by bagged consistent itemset rules. [Citation Graph (, )][DBLP]


  58. Classification by reflective convex hulls. [Citation Graph (, )][DBLP]


  59. Sitting posture analysis by pressure sensors. [Citation Graph (, )][DBLP]


  60. Estimation of class regions in feature space using rough set theory. [Citation Graph (, )][DBLP]


  61. Determination of the number of components based on class separability in mixture-based classifiers. [Citation Graph (, )][DBLP]


  62. Estimation of velocity vectors from a video stream using discontinuity of optical flow. [Citation Graph (, )][DBLP]


  63. Termination conditions for a fast k-nearest neighbor method. [Citation Graph (, )][DBLP]


  64. Geometry reconstruction of urban scenes by tracking vertical edges. [Citation Graph (, )][DBLP]


  65. Effective sampling points for two-channel spline image coding. [Citation Graph (, )][DBLP]


  66. Tabu search for solving optimization problems on Hopfield neural networks. [Citation Graph (, )][DBLP]


  67. Appropriate initial component densities of mixture modeling for pattern recognition. [Citation Graph (, )][DBLP]


  68. Polynomial-sample learnability about distance-0 and 1 DNF formulas. [Citation Graph (, )][DBLP]


  69. A Fast Nearest Neighbor Method Using Empirical Marginal Distribution. [Citation Graph (, )][DBLP]


  70. Comparison of Bagging and Boosting Algorithms on Sample and Feature Weighting. [Citation Graph (, )][DBLP]


  71. Feature and Classifier Selection in Class Decision Trees. [Citation Graph (, )][DBLP]


  72. Bagging, Random Subspace Method and Biding. [Citation Graph (, )][DBLP]


  73. Soft Feature Selection by Using a Histogram-Based Classifier. [Citation Graph (, )][DBLP]


  74. Optimal Kernel in a Class of Kernels with an Invariant Metric. [Citation Graph (, )][DBLP]


  75. Behavior Analysis of Volume Prototypes in High Dimensionality. [Citation Graph (, )][DBLP]


  76. Localized Projection Learning. [Citation Graph (, )][DBLP]


  77. Density- and Complexity-Regularization in Gaussian Mixture Bayesian Classifier. [Citation Graph (, )][DBLP]


  78. A top-down construction of class decision trees with selected features and classifiers. [Citation Graph (, )][DBLP]


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