| 2009 |
|---|
| 50 | EE | Ryotaro Kamimura:
An information-theoretic approach to feature extraction in competitive learning.
Neurocomputing 72(10-12): 2693-2704 (2009) |
| 2008 |
|---|
| 49 | EE | Ryotaro Kamimura:
Feature Discovery by Enhancement and Relaxation of Competitive Units.
IDEAL 2008: 148-155 |
| 48 | EE | Ryotaro Kamimura:
Conditional information and information loss for flexible feature extraction.
IJCNN 2008: 2074-2083 |
| 2007 |
|---|
| 47 | | Ryotaro Kamimura,
Fumihiko Yoshida,
Ryozo Kitajima:
Interpreting cabinet approval ratings by neural networks.
Artificial Intelligence and Applications 2007: 72-77 |
| 46 | | Ryotaro Kamimura:
Forced information and information loss in information-theoretic competitive learning.
Artificial Intelligence and Applications 2007: 78-84 |
| 45 | EE | Ryotaro Kamimura,
Fumihiko Yoshida,
Yamashita Toshie,
Ryozo Kitajima:
Information-Theoretic Variable Selection in Neural Networks.
FOCI 2007: 222-227 |
| 44 | EE | Ryotaro Kamimura:
Combining Hard and Soft Competition in Information-Theoretic Learning.
FOCI 2007: 578-582 |
| 43 | EE | Ryotaro Kamimura:
Forced Information and Information Loss for a Student Survey Analysis.
FOCI 2007: 630-636 |
| 42 | EE | Ryotaro Kamimura:
Partially Activated Neural Networks by Controlling Information.
ICANN (1) 2007: 480-489 |
| 41 | EE | Ryotaro Kamimura:
Controlled Competitive Learning: Extending Competitive Learning to Supervised Learning.
IJCNN 2007: 1767-1773 |
| 40 | EE | Ryotaro Kamimura,
Ryozo Kitajima:
Forced Information Maximization to Accelerate Information-Theoretic Competitive Learning.
IJCNN 2007: 1779-1784 |
| 39 | EE | Ryotaro Kamimura:
Information loss to extract distinctive features in competitive learning.
SMC 2007: 1217-1222 |
| 2006 |
|---|
| 38 | EE | Ryotaro Kamimura,
Fumihiko Yoshida,
Ryozo Kitajima:
Collective Information-Theoretic Competitive Learning: Emergency of Improved Performance by Collectively Treated Neurons.
ICONIP (1) 2006: 626-633 |
| 37 | EE | Ryotaro Kamimura:
Self-organizing by Information Maximization: Realizing Self-Organizing Maps by Information-Theoretic Competitive Learning.
ICONIP (1) 2006: 925-934 |
| 36 | EE | Ryotaro Kamimura,
Fumihiko Yoshida:
Automatic Inference of Cabinet Approval Ratings by Information-Theoretic Competitive Learning.
ICONIP (2) 2006: 897-908 |
| 35 | EE | Ryotaro Kamimura:
Supervised Information Maximization by Weighted Distance.
IJCNN 2006: 1790-1796 |
| 2005 |
|---|
| 34 | | Ryotaro Kamimura:
Modular Structure Generation and Its Application to Feature Extraction.
Artificial Intelligence and Applications 2005: 166-171 |
| 33 | | Ryotaro Kamimura:
Extracting Common and Distinctive Features by Cost-Sensitive Information Maximization.
Artificial Intelligence and Applications 2005: 172-177 |
| 32 | EE | Ryotaro Kamimura,
Sachiko Aida-Hyugaji:
Maximizing the Ratio of Information to Its Cost in Information Theoretic Competitive Learning.
ICANN (2) 2005: 215-222 |
| 31 | EE | Ryotaro Kamimura:
Unifying cost and information in information-theoretic competitive learning.
Neural Networks 18(5-6): 711-718 (2005) |
| 2004 |
|---|
| 30 | EE | Ryotaro Kamimura:
One-Epoch Learning for Supervised Information-Theoretic Competitive Learning.
ICONIP 2004: 524-529 |
| 29 | EE | Ryotaro Kamimura:
Teacher-Directed Learning with Gaussian and Sigmoid Activation Functions.
ICONIP 2004: 530-536 |
| 28 | EE | Ryotaro Kamimura,
Osamu Uchida:
Cost-Sensitive Greedy Network-Growing Algorithm with Gaussian Activation Functions.
ICONIP 2004: 653-658 |
| 27 | EE | Ryotaro Kamimura:
Improving feature extraction performance of greedy network-growing algorithm by inverse euclidean distance.
Connect. Sci. 16(2): 129-138 (2004) |
| 26 | EE | Ryotaro Kamimura:
Multi-Layered Greedy Network-Growing Algorithm: Extension of Greedy Network-Growing Algorithm to Multi-Layered Networks.
Int. J. Neural Syst. 14(1): 9-26 (2004) |
| 25 | EE | Ryotaro Kamimura:
Cooperative information control for self-organizing maps.
Neurocomputing 62: 225-265 (2004) |
| 2003 |
|---|
| 24 | EE | Ryotaro Kamimura:
Competitive Learning by Information Maximization: Eliminating Dead Neurons in Competitive Learning.
ICANN 2003: 99-106 |
| 23 | EE | Ryotaro Kamimura,
Osamu Uchida:
Improving Feature Extraction Performance of Greedy Network-Growing Algorithm.
IDEAL 2003: 1056-1061 |
| 22 | EE | Ryotaro Kamimura,
Haruhiko Takeuchi:
Generating Explicit Self-Organizing Maps by Information Maximization.
IDEAL 2003: 236-245 |
| 21 | | Ryotaro Kamimura:
Information-theoretic Competitive Learning.
Modelling and Simulation 2003: 359-365 |
| 20 | | Ryotaro Kamimura,
Seiki Hahimoto:
Economic Data Analysis and Cooperative Information Control.
Modelling and Simulation 2003: 599-605 |
| 19 | EE | Ryotaro Kamimura:
Information theoretic competitive learning in self-adaptive multi-layered networks.
Connect. Sci. 15(1): 3-26 (2003) |
| 18 | EE | Ryotaro Kamimura,
Fumihiko Yoshida:
Teacher-directed learning: information-theoretic competitive learning in supervised multi-layered networks.
Connect. Sci. 15(2-3): 117-140 (2003) |
| 17 | | Ryotaro Kamimura:
Information-Theoretic Competitive Learning with Inverse Euclidean Distance Output Units.
Neural Processing Letters 18(3): 163-204 (2003) |
| 2002 |
|---|
| 16 | EE | Ryotaro Kamimura,
Taeko Kamimura,
Haruhiko Takeuchi:
Greedy information acquisition algorithm: a new information theoretic approach to dynamic information acquisition in neural networks.
Connect. Sci. 14(2): 137-162 (2002) |
| 15 | EE | Ryotaro Kamimura:
Controlling internal representations by structural information.
Neurocomputing 48(1-4): 705-725 (2002) |
| 2001 |
|---|
| 14 | EE | Ryotaro Kamimura,
Taeko Kamimura:
Information Maximization and Language Acquisition.
ICANN 2001: 1225-1232 |
| 13 | EE | Ryotaro Kamimura,
Taeko Kamimura:
Cooperative Information Control to Coordinate Competition and Cooperation.
ICANN 2001: 835-842 |
| 12 | EE | Ryotaro Kamimura,
Taeko Kamimura,
Osamu Uchida:
Flexible feature discovery and structural information control.
Connect. Sci. 13(4): 323-347 (2001) |
| 2000 |
|---|
| 11 | EE | Ryotaro Kamimura:
Conditional Information Analysis.
IJCNN (1) 2000: 197-202 |
| 10 | EE | Ryotaro Kamimura:
Selective Information Acquisition with Application to Pattern Classification.
IJCNN (1) 2000: 203-210 |
| 1998 |
|---|
| 9 | | Ryotaro Kamimura:
Integrated Information Processors with Multi-functional Components.
ICONIP 1998: 1501-1506 |
| 8 | | Ryotaro Kamimura:
Structural Information Control to Improve Generalization.
ICONIP 1998: 643-646 |
| 1997 |
|---|
| 7 | | Ryotaro Kamimura:
Constrained Information Maximization to Control Internal Representatio.
J. Braz. Comp. Soc. 4(1): (1997) |
| 6 | EE | Ryotaro Kamimura:
Information Controller to Maximize and Minimize Information.
Neural Computation 9(6): 1357-1380 (1997) |
| 1996 |
|---|
| 5 | EE | Ryotaro Kamimura:
Unification of Information Maximization and Minimization.
NIPS 1996: 508-514 |
| 1993 |
|---|
| 4 | EE | Ryotaro Kamimura:
Generation of Internal Representation by alpha.
NIPS 1993: 271-278 |
| 1992 |
|---|
| 3 | | Ryotaro Kamimura:
Competitive Learning by Entropy Minimization.
ALT 1992: 111-122 |
| 2 | | Ryotaro Kamimura:
Complexity Term to Generate Explicit Internal Representation in Recurrent Neural Networks.
IFIP Congress (1) 1992: 336-342 |
| 1991 |
|---|
| 1 | EE | Ryotaro Kamimura:
Application of the Recurrent Neural Network to the Problem of Language Acquisition.
Conference on Analysis of Neural Network Applications 1991: 14-28 |
