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Ryotaro Kamimura: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Ryotaro Kamimura
    Modular Structure Generation and Its Application to Feature Extraction. [Citation Graph (0, 0)][DBLP]
    Artificial Intelligence and Applications, 2005, pp:166-171 [Conf]
  2. Ryotaro Kamimura
    Extracting Common and Distinctive Features by Cost-Sensitive Information Maximization. [Citation Graph (0, 0)][DBLP]
    Artificial Intelligence and Applications, 2005, pp:172-177 [Conf]
  3. Ryotaro Kamimura
    Competitive Learning by Entropy Minimization. [Citation Graph (0, 0)][DBLP]
    ALT, 1992, pp:111-122 [Conf]
  4. Ryotaro Kamimura
    Application of the Recurrent Neural Network to the Problem of Language Acquisition. [Citation Graph (0, 0)][DBLP]
    Conference on Analysis of Neural Network Applications, 1991, pp:14-28 [Conf]
  5. Ryotaro Kamimura
    Competitive Learning by Information Maximization: Eliminating Dead Neurons in Competitive Learning. [Citation Graph (0, 0)][DBLP]
    ICANN, 2003, pp:99-106 [Conf]
  6. Ryotaro Kamimura, Sachiko Aida-Hyugaji
    Maximizing the Ratio of Information to Its Cost in Information Theoretic Competitive Learning. [Citation Graph (0, 0)][DBLP]
    ICANN (2), 2005, pp:215-222 [Conf]
  7. Ryotaro Kamimura, Taeko Kamimura
    Cooperative Information Control to Coordinate Competition and Cooperation. [Citation Graph (0, 0)][DBLP]
    ICANN, 2001, pp:835-842 [Conf]
  8. Ryotaro Kamimura, Taeko Kamimura
    Information Maximization and Language Acquisition. [Citation Graph (0, 0)][DBLP]
    ICANN, 2001, pp:1225-1232 [Conf]
  9. Ryotaro Kamimura
    One-Epoch Learning for Supervised Information-Theoretic Competitive Learning. [Citation Graph (0, 0)][DBLP]
    ICONIP, 2004, pp:524-529 [Conf]
  10. Ryotaro Kamimura
    Teacher-Directed Learning with Gaussian and Sigmoid Activation Functions. [Citation Graph (0, 0)][DBLP]
    ICONIP, 2004, pp:530-536 [Conf]
  11. Ryotaro Kamimura
    Self-organizing by Information Maximization: Realizing Self-Organizing Maps by Information-Theoretic Competitive Learning. [Citation Graph (0, 0)][DBLP]
    ICONIP (1), 2006, pp:925-934 [Conf]
  12. Ryotaro Kamimura
    Structural Information Control to Improve Generalization. [Citation Graph (0, 0)][DBLP]
    ICONIP, 1998, pp:643-646 [Conf]
  13. Ryotaro Kamimura
    Integrated Information Processors with Multi-functional Components. [Citation Graph (0, 0)][DBLP]
    ICONIP, 1998, pp:1501-1506 [Conf]
  14. Ryotaro Kamimura, Osamu Uchida
    Cost-Sensitive Greedy Network-Growing Algorithm with Gaussian Activation Functions. [Citation Graph (0, 0)][DBLP]
    ICONIP, 2004, pp:653-658 [Conf]
  15. Ryotaro Kamimura, Fumihiko Yoshida
    Automatic Inference of Cabinet Approval Ratings by Information-Theoretic Competitive Learning. [Citation Graph (0, 0)][DBLP]
    ICONIP (2), 2006, pp:897-908 [Conf]
  16. Ryotaro Kamimura, Fumihiko Yoshida, Ryozo Kitajima
    Collective Information-Theoretic Competitive Learning: Emergency of Improved Performance by Collectively Treated Neurons. [Citation Graph (0, 0)][DBLP]
    ICONIP (1), 2006, pp:626-633 [Conf]
  17. Ryotaro Kamimura, Haruhiko Takeuchi
    Generating Explicit Self-Organizing Maps by Information Maximization. [Citation Graph (0, 0)][DBLP]
    IDEAL, 2003, pp:236-245 [Conf]
  18. Ryotaro Kamimura, Osamu Uchida
    Improving Feature Extraction Performance of Greedy Network-Growing Algorithm. [Citation Graph (0, 0)][DBLP]
    IDEAL, 2003, pp:1056-1061 [Conf]
  19. Ryotaro Kamimura
    Complexity Term to Generate Explicit Internal Representation in Recurrent Neural Networks. [Citation Graph (0, 0)][DBLP]
    IFIP Congress (1), 1992, pp:336-342 [Conf]
  20. Ryotaro Kamimura
    Conditional Information Analysis. [Citation Graph (0, 0)][DBLP]
    IJCNN (1), 2000, pp:197-202 [Conf]
  21. Ryotaro Kamimura
    Selective Information Acquisition with Application to Pattern Classification. [Citation Graph (0, 0)][DBLP]
    IJCNN (1), 2000, pp:203-210 [Conf]
  22. Ryotaro Kamimura
    Information-theoretic Competitive Learning. [Citation Graph (0, 0)][DBLP]
    Modelling and Simulation, 2003, pp:359-365 [Conf]
  23. Ryotaro Kamimura, Seiki Hahimoto
    Economic Data Analysis and Cooperative Information Control. [Citation Graph (0, 0)][DBLP]
    Modelling and Simulation, 2003, pp:599-605 [Conf]
  24. Ryotaro Kamimura
    Generation of Internal Representation by alpha. [Citation Graph (0, 0)][DBLP]
    NIPS, 1993, pp:271-278 [Conf]
  25. Ryotaro Kamimura
    Unification of Information Maximization and Minimization. [Citation Graph (0, 0)][DBLP]
    NIPS, 1996, pp:508-514 [Conf]
  26. Ryotaro Kamimura
    Improving feature extraction performance of greedy network-growing algorithm by inverse euclidean distance. [Citation Graph (0, 0)][DBLP]
    Connect. Sci., 2004, v:16, n:2, pp:129-138 [Journal]
  27. Ryotaro Kamimura, Taeko Kamimura, Haruhiko Takeuchi
    Greedy information acquisition algorithm: a new information theoretic approach to dynamic information acquisition in neural networks. [Citation Graph (0, 0)][DBLP]
    Connect. Sci., 2002, v:14, n:2, pp:137-162 [Journal]
  28. Ryotaro Kamimura, Taeko Kamimura, Osamu Uchida
    Flexible feature discovery and structural information control. [Citation Graph (0, 0)][DBLP]
    Connect. Sci., 2001, v:13, n:4, pp:323-347 [Journal]
  29. Ryotaro Kamimura, Fumihiko Yoshida
    Teacher-directed learning: information-theoretic competitive learning in supervised multi-layered networks. [Citation Graph (0, 0)][DBLP]
    Connect. Sci., 2003, v:15, n:2-3, pp:117-140 [Journal]
  30. Ryotaro Kamimura
    Information theoretic competitive learning in self-adaptive multi-layered networks. [Citation Graph (0, 0)][DBLP]
    Connect. Sci., 2003, v:15, n:1, pp:3-26 [Journal]
  31. Ryotaro Kamimura
    Multi-Layered Greedy Network-Growing Algorithm: Extension of Greedy Network-Growing Algorithm to Multi-Layered Networks. [Citation Graph (0, 0)][DBLP]
    Int. J. Neural Syst., 2004, v:14, n:1, pp:9-26 [Journal]
  32. Ryotaro Kamimura
    Controlling internal representations by structural information. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2002, v:48, n:1-4, pp:705-725 [Journal]
  33. Ryotaro Kamimura
    Cooperative information control for self-organizing maps. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2004, v:62, n:, pp:225-265 [Journal]
  34. Ryotaro Kamimura
    Constrained Information Maximization to Control Internal Representatio. [Citation Graph (0, 0)][DBLP]
    J. Braz. Comp. Soc., 1997, v:4, n:1, pp:- [Journal]
  35. Ryotaro Kamimura
    Information Controller to Maximize and Minimize Information. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 1997, v:9, n:6, pp:1357-1380 [Journal]
  36. Ryotaro Kamimura
    Unifying cost and information in information-theoretic competitive learning. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 2005, v:18, n:5-6, pp:711-718 [Journal]
  37. Ryotaro Kamimura
    Information-Theoretic Competitive Learning with Inverse Euclidean Distance Output Units. [Citation Graph (0, 0)][DBLP]
    Neural Processing Letters, 2003, v:18, n:3, pp:163-204 [Journal]
  38. Ryotaro Kamimura
    Forced information and information loss in information-theoretic competitive learning. [Citation Graph (0, 0)][DBLP]
    Artificial Intelligence and Applications, 2007, pp:78-84 [Conf]
  39. Ryotaro Kamimura, Fumihiko Yoshida, Ryozo Kitajima
    Interpreting cabinet approval ratings by neural networks. [Citation Graph (0, 0)][DBLP]
    Artificial Intelligence and Applications, 2007, pp:72-77 [Conf]
  40. Ryotaro Kamimura
    Partially Activated Neural Networks by Controlling Information. [Citation Graph (0, 0)][DBLP]
    ICANN (1), 2007, pp:480-489 [Conf]
  41. Ryotaro Kamimura
    Combining Hard and Soft Competition in Information-Theoretic Learning. [Citation Graph (0, 0)][DBLP]
    FOCI, 2007, pp:578-582 [Conf]
  42. Ryotaro Kamimura
    Forced Information and Information Loss for a Student Survey Analysis. [Citation Graph (0, 0)][DBLP]
    FOCI, 2007, pp:630-636 [Conf]
  43. Ryotaro Kamimura, Fumihiko Yoshida, Yamashita Toshie, Ryozo Kitajima
    Information-Theoretic Variable Selection in Neural Networks. [Citation Graph (0, 0)][DBLP]
    FOCI, 2007, pp:222-227 [Conf]

  44. Generation of Comprehensible Representations by Supposed Maximum Information. [Citation Graph (, )][DBLP]


  45. Enhanced Visualization by Combing SOM and Mixture Models. [Citation Graph (, )][DBLP]


  46. Collective Activations to Generate Self-Organizing Maps. [Citation Graph (, )][DBLP]


  47. Partially Enhanced Competitive Learning. [Citation Graph (, )][DBLP]


  48. Feature Detection by Structural Enhanced Information. [Citation Graph (, )][DBLP]


  49. Feature Discovery by Enhancement and Relaxation of Competitive Units. [Citation Graph (, )][DBLP]


  50. Forced Information Maximization to Accelerate Information-Theoretic Competitive Learning. [Citation Graph (, )][DBLP]


  51. Controlled Competitive Learning: Extending Competitive Learning to Supervised Learning. [Citation Graph (, )][DBLP]


  52. Supervised Information Maximization by Weighted Distance. [Citation Graph (, )][DBLP]


  53. Conditional information and information loss for flexible feature extraction. [Citation Graph (, )][DBLP]


  54. Information loss to extract distinctive features in competitive learning. [Citation Graph (, )][DBLP]


  55. Structural Enhanced Information to Detect Features in Competitive Learning. [Citation Graph (, )][DBLP]


  56. Self-supervised learning by information enhancement: Target-Generating and Spontaneous learning for Competitive Learning. [Citation Graph (, )][DBLP]


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