The SCEAS System
Navigation Menu

Search the dblp DataBase

Title:
Author:

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]


Search in 0.006secs, Finished in 0.009secs
NOTICE1
System may not be available sometimes or not working properly, since it is still in development with continuous upgrades
NOTICE2
The rankings that are presented on this page should NOT be considered as formal since the citation info is incomplete in DBLP
 
System created by asidirop@csd.auth.gr [http://users.auth.gr/~asidirop/] © 2002
for Data Engineering Laboratory, Department of Informatics, Aristotle University © 2002