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2020 – today
- 2024
[c121]Ryotaro Kamimura:
Forced and Natural Creative-Prototype Learning for Interpreting Multi-Layered Neural Networks. IIAI-AAI 2024: 343-350- 2023
- [j58]Ryotaro Kamimura
:
Contradiction neutralization for interpreting multi-layered neural networks. Appl. Intell. 53(23): 28349-28376 (2023) - [j57]Ryotaro Kamimura:
Impartial competitive learning in multi-layered neural networks. Connect. Sci. 35(1) (2023) - [j56]Ryotaro Kamimura:
Destructive computing with winner-lose-all competition in multi-layered neural networks. Int. J. Hybrid Intell. Syst. 19(3): 145-166 (2023) - [c120]Ryotaro Kamimura:
Repeated Potentiality Augmentation for Multi-layered Neural Networks. FICC (2) 2023: 117-134 - 2022
- [j55]Ryotaro Kamimura:
Multi-level selective potentiality maximization for interpreting multi-layered neural networks. Appl. Intell. 52(12): 13961-13986 (2022) - [j54]Ryotaro Kamimura:
Cost-forced and repeated selective information minimization and maximization for multi-layered neural networks. Int. J. Hybrid Intell. Syst. 18(1-2): 69-95 (2022) - [j53]Ryotaro Kamimura:
Cost-forced collective potentiality maximization by complementary potentiality minimization for interpreting multi-layered neural networks. Neurocomputing 480: 234-256 (2022) - [c119]Ryotaro Kamimura, Ryozo Kitajima:
Min-Max Cost and Information Control in Multi-layered Neural Networks. FTC (1) 2022: 1-17 - [c118]Ryotaro Kamimura, Ryozo Kitajima:
Serially Disentangled Learning for Multi-Layered Neural Networks. IEA/AIE 2022: 669-681 - 2021
- [j52]Ryotaro Kamimura:
Partially black-boxed collective interpretation and its application to SOM-based convolutional neural networks. Neurocomputing 450: 336-353 (2021) - [c117]Ryotaro Kamimura, Ryozo Kitajima:
Forced Selective Information Reduction for Interpreting Multi-Layered Neural Networks. IIAI-AAI-Winter 2021: 24-40 - [c116]Ryotaro Kamimura:
Selective Information Control and Network Compression in Multi-layered Neural Networks. IntelliSys (1) 2021: 184-204 - [c115]Ryotaro Kamimura:
Selective Information Control and Layer-Wise Partial Collective Compression for Multi-Layered Neural Networks. ISDA 2021: 121-131 - 2020
- [j51]Ryotaro Kamimura:
Minimum interpretation by autoencoder-based serial and enhanced mutual information production. Appl. Intell. 50(8): 2423-2448 (2020) - [j50]Ryotaro Kamimura, Haruhiko Takeuchi:
Improving collective interpretation by extended potentiality assimilation for multi-layered neural networks. Connect. Sci. 32(2): 174-203 (2020) - [j49]Ryotaro Kamimura:
Cost-conscious mutual information maximization for improving collective interpretation of multi-layered neural networks. Neurocomputing 409: 259-274 (2020) - [c114]Ryotaro Kamimura:
Cost-Conscious Internal Information Maximization for Disentangling and Interpreting Multi-layered Neural Networks. HIS 2020: 606-616 - [c113]Ryotaro Kamimura:
Compressing and Interpreting SOM-Based Convolutional Neural Networks. IEA/AIE 2020: 732-744 - [c112]Ryotaro Kamimura:
Disentangled Representations by Pseudo-Maximum Mutual Information for Interpreting Multi-Layered Neural Networks. IIAI-AAI 2020: 436-443 - [c111]Ryotaro Kamimura:
Bidirectional Estimation of Partially Black-Boxed Layers of SOM-Based Convolutional Neural Networks. IntelliSys (1) 2020: 407-427 - [c110]Ryotaro Kamimura:
Connective Potential Information for Collectively Interpreting Multi-Layered Neural Networks. SSCI 2020: 3033-3042
2010 – 2019
- 2019
- [j48]Ryotaro Kamimura, Haruhiko Takeuchi:
Sparse semi-autoencoders to solve the vanishing information problem in multi-layered neural networks. Appl. Intell. 49(7): 2522-2545 (2019) - [j47]Ryotaro Kamimura:
SOM-based information maximization to improve and interpret multi-layered neural networks: From information reduction to information augmentation approach to create new information. Expert Syst. Appl. 125: 397-411 (2019) - [j46]Ryotaro Kamimura:
Neural self-compressor: Collective interpretation by compressing multi-layered neural networks into non-layered networks. Neurocomputing 323: 12-36 (2019) - [j45]Ryotaro Kamimura:
Supposed Maximum Mutual Information for Improving Generalization and Interpretation of Multi-Layered Neural Networks. J. Artif. Intell. Soft Comput. Res. 9(2): 123-147 (2019) - [c109]Ryotaro Kamimura:
Information Compression for Intelligible Multi-Layered Neural Networks. IIAI-AAI 2019: 635-642 - [c108]Ryozo Kitajima, Ryotaro Kamimura, Hiroyuki Sakai:
Relationship Between Management Policies and Profitability for Second Section-Listed Manufacturing Companies of the Tokyo Stock Exchange (2016 Results). IIAI-AAI 2019: 697-700 - [c107]Ryotaro Kamimura:
Mutual Information Generation for Improving Generalization and Interpretation in Neural Networks. IJCNN 2019: 1-8 - [c106]Ryotaro Kamimura:
Interpreting Collectively Compressed Multi-Layered Neural Networks. CIS/RAM 2019: 95-100 - 2018
- [j44]Ryotaro Kamimura, Tsubasa Kitago:
Self-Assimilation for Solving Excessive Information Acquisition in Potential Learning. J. Artif. Intell. Soft Comput. Res. 8(1): 5-29 (2018) - [c105]Ryotaro Kamimura, Haruhiko Takeuchi:
Autoeconder-Based Excessive Information Generation for Improving and Interpreting Multi-layered Neural Networks. IIAI-AAI 2018: 518-523 - [c104]Ryotaro Kamimura, Haruhiko Takeuchi:
Excessive, Selective and Collective Information Processing to Improve and Interpret Multi-layered Neural Networks. IntelliSys (1) 2018: 664-675 - [c103]Ryotaro Kamimura:
Autoeoncoders and Information Augmentation for Improved Generalization and Interpretation in Multi-layered Neural Networks. ISCBI 2018: 52-58 - [c102]Ryotaro Kamimura, Ryozo Kitajima, Hiroyuki Sakai:
Local Selective Learning for Interpreting Multi-Layered Neural Networks. SCIS&ISIS 2018: 115-122 - [c101]Ryotaro Kamimura, Haruhiko Takeuchi:
Correlation-Constrained Mutual Information Maximization for Interpretable Multi-Layered Neural Networks. SCIS&ISIS 2018: 123-130 - [c100]Ryotaro Kamimura:
Information-Theoretic Self-compression of Multi-layered Neural Networks. TPNC 2018: 401-413 - 2017
- [j43]Ryotaro Kamimura:
Collective mutual information maximization to unify passive and positive approaches for improving interpretation and generalization. Neural Networks 90: 56-71 (2017) - [c99]Ryotaro Kamimura:
Direct Potentiality Assimilation for Improving Multi-Layered Neural Networks. FedCSIS (Position Papers) 2017: 19-23 - [c98]Ryotaro Kamimura, Haruhiko Takeuchi:
Supervised semi-autoencoder learning for multi-layered neural networks. IFSA-SCIS 2017: 1-8 - [c97]Ryotaro Kamimura:
Selective and cooperative potentiality maximization for improving interpretation and generalization. IJCNN 2017: 147-153 - [c96]Ryotaro Kamimura:
Potential layer-wise supervised learning for training multi-layered neural networks. IJCNN 2017: 2568-2575 - [c95]Ryotaro Kamimura:
Mutual information maximization for improving and interpreting multi-layered neural networks. SSCI 2017: 1-7 - 2016
- [j42]Ryozo Kitajima, Ryotaro Kamimura, Osamu Uchida, Fujio Toriumi:
Identifying Important Tweets by Considering the Potentiality of Neurons. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. 99-A(8): 1555-1559 (2016) - [c94]Ryotaro Kamimura:
Simple and Stable Internal Representation by Potential Mutual Information Maximization. EANN 2016: 309-316 - [c93]Ryotaro Kamimura:
Solving the Vanishing Information Problem with Repeated Potential Mutual Information Maximization. ICONIP (4) 2016: 442-451 - [c92]Ryotaro Kamimura:
Collective Interpretation and Potential Joint Information Maximization. Intelligent Information Processing 2016: 12-21 - [c91]Ryotaro Kamimura:
Repeated potentiality assimilation: Simplifying learning procedures by positive, independent and indirect operation for improving generalization and interpretation. IJCNN 2016: 803-810 - 2015
- [j41]Ryotaro Kamimura:
Improving visualisation and prediction performance of supervised self-organising map by modified contradiction resolution. Connect. Sci. 27(1): 40-67 (2015) - [j40]Ryozo Kitajima, Ryotaro Kamimura:
Accumulative Information Enhancement In The Self-Organizing Maps And Its Application To The Analysis Of Mission Statements. J. Artif. Intell. Soft Comput. Res. 5(3): 161 (2015) - [c90]Ryotaro Kamimura:
Pseudo-potentiality maximization for improved interpretation and generalization in neural networks. IWCIA 2015: 21-28 - [c89]Ryotaro Kamimura:
Simplified and gradual information control for improving generalization performance of multi-layered neural networks. IJCNN 2015: 1-7 - [c88]Ryotaro Kamimura, Ryozo Kitajima:
Selective potentiality maximization for input neuron selection in self-organizing maps. IJCNN 2015: 1-8 - [c87]Ryotaro Kamimura:
Self-Organized Mutual Information Maximization Learning for Improved Generalization Performance. SMC 2015: 1613-1618 - [c86]Ryotaro Kamimura:
Self-Organizing Selective Potentiality Learning to Detect Important Input Neurons. SMC 2015: 1619-1626 - [c85]Ryozo Kitajima, Ryotaro Kamimura, Osamu Uchida, Fujio Toriumi:
Neural potential learning for tweets classification and interpretation. SoCPaR 2015: 141-148 - 2014
- [j39]Ryotaro Kamimura:
Input information maximization for improving self-organizing maps. Appl. Intell. 41(2): 421-438 (2014) - [c84]Ryotaro Kamimura:
Simplified Information Acquisition Method to Improve Prediction Performance: Direct Use of Hidden Neuron Outputs and Separation of Information Acquisition and Use Phase. ANNIIP 2014: 78-87 - [c83]Ryotaro Kamimura:
Explicit knowledge extraction in information-theoretic supervised multi-layered SOM. FOCI 2014: 78-83 - [c82]Ryotaro Kamimura:
Information acquisition performance by supervised information-theoretic self-organizing maps. NaBIC 2014: 151-157 - [c81]Ryotaro Kamimura:
Information-theoretic multi-layered supervised self-organizing maps for improved prediction performance and explicit internal representation. SMC 2014: 953-958 - [c80]Ryotaro Kamimura, Taeko Kamimura:
Embedded information enhancement for neuron selection in self-organizing maps. SMC 2014: 959-965 - 2013
- [j38]Ryotaro Kamimura:
Similarity interaction in information-theoretic self-organizing maps. Int. J. Gen. Syst. 42(3): 239-267 (2013) - [j37]Ryotaro Kamimura:
Repeated comprehensibility maximization in competitive learning. Neural Comput. Appl. 22(5): 911-932 (2013) - [j36]Ryotaro Kamimura:
Controlling Relations between the Individuality and Collectivity of Neurons and its Application to Self-Organizing Maps. Neural Process. Lett. 38(2): 177-203 (2013) - [c79]Ryotaro Kamimura:
Dependent input neuron selection in contradiction resolution. IWCIA 2013: 45-50 - [c78]Ryotaro Kamimura:
Contradiction resolution with explicit and limited evaluation and its application to SOM. IJCNN 2013: 1-8 - [c77]Ryotaro Kamimura:
Contradiction Resolution with Dependent Input Neuron Selection for Self-Organizing Maps. SMC 2013: 1353-1360 - 2012
- [j35]Ryotaro Kamimura:
Double enhancement learning for explicit internal representations: unifying self-enhancement and information enhancement to incorporate information on input variables. Appl. Intell. 36(4): 834-856 (2012) - [j34]Ryotaro Kamimura:
Comprehensibility maximization and humanly comprehensible representations. Int. J. Gen. Syst. 41(3): 265-287 (2012) - [j33]Ryotaro Kamimura:
Relative information maximization and its application to the extraction of explicit class structure in SOM. Neurocomputing 82: 37-51 (2012) - [c76]Ryotaro Kamimura:
Separation and Unification of Individuality and Collectivity and Its Application to Explicit Class Structure in Self-Organizing Maps. ICANN (2) 2012: 387-394 - [c75]Ryotaro Kamimura:
Contradiction Resolution for Foreign Exchange Rates Estimation. IJCCI 2012: 529-535 - [c74]Ryotaro Kamimura:
Interaction of individually and collectively treated neurons for explicit class structure in self-organizing maps. IJCNN 2012: 1-8 - [c73]Ryotaro Kamimura:
Contradiction resolution and its application to self-organizing maps. SMC 2012: 1966-1971 - 2011
- [j32]Ryotaro Kamimura:
Structural enhanced information and its application to improved visualization of self-organizing maps. Appl. Intell. 34(1): 102-115 (2011) - [j31]Ryotaro Kamimura:
Self-enhancement learning: target-creating learning and its application to self-organizing maps. Biol. Cybern. 104(4-5): 305-338 (2011) - [j30]Ryotaro Kamimura:
Constrained information maximization by free energy minimization. Int. J. Gen. Syst. 40(7): 701-725 (2011) - [j29]Ryotaro Kamimura:
Supposed maximum information for comprehensible representations in SOM. Neurocomputing 74(7): 1116-1134 (2011) - [j28]Ryotaro Kamimura:
Selective information enhancement learning for creating interpretable representations in competitive learning. Neural Networks 24(4): 387-405 (2011) - [c72]Ryotaro Kamimura:
Relative Information Maximization and Its Application to the Detection of Explicit Class Structure in SOM. FOCI 2011: 74-79 - [c71]Ryotaro Kamimura:
Explicit Class Structure by Weighted Cooperative Learning. ICANN (1) 2011: 109-116 - [c70]Ryotaro Kamimura:
Individually and Collectively Treated Neurons and its Application to SOM . IJCCI (NCTA) 2011: 24-30 - [c69]Ryotaro Kamimura:
Cooperation control and enhanced class structure in self-organizing maps. IJCNN 2011: 689-695 - [c68]Ryotaro Kamimura:
Explicit class structure with closeness and similarity between neurons. NaBIC 2011: 92-98 - 2010
- [j27]Ryotaro Kamimura:
Information enhancement for interpreting competitive learning. Int. J. Gen. Syst. 39(7): 705-728 (2010) - [j26]Ryotaro Kamimura:
Information-theoretic enhancement learning and its application to visualization of self-organizing maps. Neurocomputing 73(13-15): 2642-2664 (2010) - [c67]Ryotaro Kamimura:
Generation of Comprehensible Representations by Supposed Maximum Information. ICANN (2) 2010: 333-342 - [c66]Ryotaro Kamimura:
Pseudo-network Growing for Gradual Interpretation of Input Patterns. ICONIP (2) 2010: 375-382 - [c65]Ryotaro Kamimura:
Information-Theoretic Competitive and Cooperative Learning for Self-Organizing Maps. ICONIP (2) 2010: 423-430 - [c64]Ryotaro Kamimura:
Explicit class structure produced by information-theoretic competitive and cooperative learning. NaBIC 2010: 628-633
2000 – 2009
- 2009
- [j25]Ryotaro Kamimura:
An information-theoretic approach to feature extraction in competitive learning. Neurocomputing 72(10-12): 2693-2704 (2009) - [j24]Ryotaro Kamimura:
Relative Relaxation and Weighted Information Loss to Simplify and Stabilize Feature Detection. J. Adv. Comput. Intell. Intell. Informatics 13(4): 489-498 (2009) - [j23]Ryotaro Kamimura:
Feature Discovery by Information Loss. J. Comput. 4(10): 943-953 (2009) - [j22]Ryotaro Kamimura:
Enhancing and Relaxing Competitive Units for Feature Discovery. Neural Process. Lett. 30(1): 37-57 (2009) - [c63]Ryotaro Kamimura:
Information Enhancement Learning: Local Enhanced Information to Detect the Importance of Input Variables in Competitive Learning. EANN 2009: 86-97 - [c62]Ryotaro Kamimura:
Selective enhancement learning in competitive learning. IJCNN 2009: 1497-1502 - [c61]Ryotaro Kamimura:
Self-enhancement learning: Self-supervised and target-creating learning. IJCNN 2009: 1503-1509 - [c60]Ryotaro Kamimura:
Self-supervised learning by information enhancement: Target-Generating and Spontaneous learning for Competitive Learning. SMC 2009: 113-119 - [c59]Ryotaro Kamimura:
Structural Enhanced Information to Detect Features in Competitive Learning. SMC 2009: 3395-3401 - 2008
- [c58]Ryotaro Kamimura:
Partially Enhanced Competitive Learning. ICONIP (2) 2008: 163-170 - [c57]Ryotaro Kamimura:
Feature Detection by Structural Enhanced Information. ICONIP (2) 2008: 171-178 - [c56]Ryotaro Kamimura:
Enhanced Visualization by Combing SOM and Mixture Models. ICONIP (2) 2008: 268-275 - [c55]Ryotaro Kamimura:
Collective Activations to Generate Self-Organizing Maps. ICONIP (2) 2008: 943-950 - [c54]Ryotaro Kamimura:
Feature Discovery by Enhancement and Relaxation of Competitive Units. IDEAL 2008: 148-155 - [c53]Ryotaro Kamimura:
Conditional information and information loss for flexible feature extraction. IJCNN 2008: 2074-2083 - [c52]Ryotaro Kamimura:
Interpreting and improving multi-layered networks by free energy-based competitive learning. SMC 2008: 1812-1818 - [c51]Ryotaro Kamimura:
Mutual information maximization by free energy-based competitive learning for self-organizing maps. SMC 2008: 1819-1825 - 2007
- [j21]Ryotaro Kamimura, Osamu Uchida, Seiki Hashimoto:
Greedy network-growing algorithm with Minkowski distances. Int. J. Gen. Syst. 36(2): 157-177 (2007) - [c50]Ryotaro Kamimura, Fumihiko Yoshida, Ryozo Kitajima:
Interpreting cabinet approval ratings by neural networks. Artificial Intelligence and Applications 2007: 72-77 - [c49]Ryotaro Kamimura:
Forced information and information loss in information-theoretic competitive learning. Artificial Intelligence and Applications 2007: 78-84 - [c48]Ryotaro Kamimura, Fumihiko Yoshida, Yamashita Toshie, Ryozo Kitajima:
Information-Theoretic Variable Selection in Neural Networks. FOCI 2007: 222-227 - [c47]Ryotaro Kamimura:
Combining Hard and Soft Competition in Information-Theoretic Learning. FOCI 2007: 578-582 - [c46]Ryotaro Kamimura:
Forced Information and Information Loss for a Student Survey Analysis. FOCI 2007: 630-636 - [c45]Ryotaro Kamimura:
Partially Activated Neural Networks by Controlling Information. ICANN (1) 2007: 480-489 - [c44]Ryotaro Kamimura:
Controlled Competitive Learning: Extending Competitive Learning to Supervised Learning. IJCNN 2007: 1767-1773 - [c43]Ryotaro Kamimura, Ryozo Kitajima:
Forced Information Maximization to Accelerate Information-Theoretic Competitive Learning. IJCNN 2007: 1779-1784 - [c42]Ryotaro Kamimura:
Information loss to extract distinctive features in competitive learning. SMC 2007: 1217-1222 - 2006
- [j20]Ryotaro Kamimura:
Cooperative information maximization with Gaussian activation functions for self-organizing maps. IEEE Trans. Neural Networks 17(4): 909-918 (2006) - [c41]Ryotaro Kamimura, Fumihiko Yoshida, Ryozo Kitajima:
Collective Information-Theoretic Competitive Learning: Emergency of Improved Performance by Collectively Treated Neurons. ICONIP (1) 2006: 626-633 - [c40]Ryotaro Kamimura, Fumihiko Yoshida:
Automatic Inference of Cabinet Approval Ratings by Information-Theoretic Competitive Learning. ICONIP (2) 2006: 897-908 - [c39]Ryotaro Kamimura:
Self-organizing by Information Maximization: Realizing Self-Organizing Maps by Information-Theoretic Competitive Learning. ICONIP (1) 2006: 925-934 - [c38]Ryotaro Kamimura:
Supervised Information Maximization by Weighted Distance. IJCNN 2006: 1790-1796 - [c37]Ryotaro Kamimura:
Controlling Excessive Information by Surface Information Criterion for Information-Theoretic Self-Organizing Maps. SMC 2006: 5130-5134 - [c36]Ryotaro Kamimura:
Student Survey by Information-Theoretic Competitive Learning. SMC 2006: 5135-5140 - 2005
- [j19]Ryotaro Kamimura:
Improving information-theoretic competitive learning by accentuated information maximization. Int. J. Gen. Syst. 34(3): 219-233 (2005) - [j18]Ryotaro Kamimura:
Unifying cost and information in information-theoretic competitive learning. Neural Networks 18(5-6): 711-718 (2005) - [c35]Ryotaro Kamimura:
Modular Structure Generation and Its Application to Feature Extraction. Artificial Intelligence and Applications 2005: 166-171 - [c34]Ryotaro Kamimura:
Extracting Common and Distinctive Features by Cost-Sensitive Information Maximization. Artificial Intelligence and Applications 2005: 172-177 - [c33]Ryotaro Kamimura, Sachiko Aida-Hyugaji:
Maximizing the Ratio of Information to Its Cost in Information Theoretic Competitive Learning. ICANN (2) 2005: 215-222 - 2004
- [j17]Ryotaro Kamimura:
Improving feature extraction performance of greedy network-growing algorithm by inverse euclidean distance. Connect. Sci. 16(2): 129-138 (2004) - [j16]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) - [j15]Ryotaro Kamimura:
Cooperative information control for self-organizing maps. Neurocomputing 62: 225-265 (2004) - [c32]Ryotaro Kamimura:
One-Epoch Learning for Supervised Information-Theoretic Competitive Learning. ICONIP 2004: 524-529 - [c31]Ryotaro Kamimura:
Teacher-Directed Learning with Gaussian and Sigmoid Activation Functions. ICONIP 2004: 530-536 - [c30]Ryotaro Kamimura, Osamu Uchida:
Cost-Sensitive Greedy Network-Growing Algorithm with Gaussian Activation Functions. ICONIP 2004: 653-658 - 2003
- [j14]Ryotaro Kamimura:
Progressive Feature Extraction with a Greedy Network-growing Algorithm. Complex Syst. 14(2) (2003) - [j13]Ryotaro Kamimura:
Information theoretic competitive learning in self-adaptive multi-layered networks. Connect. Sci. 15(1): 3-26 (2003) - [j12]Ryotaro Kamimura, Fumihiko Yoshida:
Teacher-directed learning: information-theoretic competitive learning in supervised multi-layered networks. Connect. Sci. 15(2-3): 117-140 (2003) - [j11]Ryotaro Kamimura:
Information-Theoretic Competitive Learning with Inverse Euclidean Distance Output Units. Neural Process. Lett. 18(3): 163-204 (2003) - [c29]Ryotaro Kamimura:
Competitive Learning by Information Maximization: Eliminating Dead Neurons in Competitive Learning. ICANN 2003: 99-106 - [c28]Ryotaro Kamimura, Haruhiko Takeuchi:
Generating Explicit Self-Organizing Maps by Information Maximization. IDEAL 2003: 236-245 - [c27]Ryotaro Kamimura, Osamu Uchida:
Improving Feature Extraction Performance of Greedy Network-Growing Algorithm. IDEAL 2003: 1056-1061 - [c26]Ryotaro Kamimura:
Information-theoretic Competitive Learning. Modelling and Simulation 2003: 359-365 - [c25]Ryotaro Kamimura, Seiki Hashimoto:
Economic Data Analysis and Cooperative Information Control. Modelling and Simulation 2003: 599-605 - 2002
- [j10]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) - [j9]Ryotaro Kamimura:
Controlling internal representations by structural information. Neurocomputing 48(1-4): 705-725 (2002) - 2001
- [j8]Ryotaro Kamimura, Taeko Kamimura, Osamu Uchida:
Flexible feature discovery and structural information control. Connect. Sci. 13(4): 323-347 (2001) - [c24]Ryotaro Kamimura, Taeko Kamimura:
Cooperative Information Control to Coordinate Competition and Cooperation. ICANN 2001: 835-842 - [c23]Ryotaro Kamimura, Taeko Kamimura:
Information Maximization and Language Acquisition. ICANN 2001: 1225-1232 - 2000
- [c22]Ryotaro Kamimura:
Conditional Information Analysis. IJCNN (1) 2000: 197-202 - [c21]Ryotaro Kamimura:
Selective Information Acquisition with Application to Pattern Classification. IJCNN (1) 2000: 203-210 - [c20]Ryotaro Kamimura, Taeko Kamimura:
Information theoretic rule discovery in neural networks. SMC 2000: 2569-2574
1990 – 1999
- 1999
- [c19]Ryotaro Kamimura:
Mediated and multi-level information processing. IJCNN 1999: 1397-1402 - [c18]Ryotaro Kamimura:
Controlling simple structural information to improve generalization performance. IJCNN 1999: 1403-1408 - 1998
- [j7]Ryotaro Kamimura:
Minimizing alpha-Information for Generalization and Interpretation. Algorithmica 22(1/2): 173-197 (1998) - [c17]Ryotaro Kamimura:
Structural Information Control to Improve Generalization. ICONIP 1998: 643-646 - [c16]Ryotaro Kamimura:
Integrated Information Processors with Multi-functional Components. ICONIP 1998: 1501-1506 - 1997
- [j6]Ryotaro Kamimura:
Controlling α-entropy with a Neural α-Feature Detector. Complex Syst. 11(1) (1997) - [j5]Ryotaro Kamimura:
Constrained Information Maximization to Control Internal Representatio. J. Braz. Comput. Soc. 4(1) (1997) - [j4]Ryotaro Kamimura:
Information Controller to Maximize and Minimize Information. Neural Comput. 9(6): 1357-1380 (1997) - [c15]Ryotaro Kamimura:
D-entropy minimization: integration of mutual information maximization and minimization. ICNN 1997: 1056-1061 - [c14]Ryotaro Kamimura:
D-entropy controller for interpretation and generalization. ICNN 1997: 1948-1953 - 1996
- [c13]Ryotaro Kamimura, Shohachiro Nakanishi:
Constrained information maximization. ICNN 1996: 740-744 - [c12]Ryotaro Kamimura, Shohachiro Nakanishi:
Kernel feature detector: extracting kernel features by minimizing α-information. ICNN 1996: 2182-2187 - [c11]Ryotaro Kamimura:
Unification of Information Maximization and Minimization. NIPS 1996: 508-514 - 1995
- [j3]Ryotaro Kamimura, Toshiyuki Takagi, Shohachiro Nakanishi:
Improving Generalization Performance by Information Minimization. IEICE Trans. Inf. Syst. 78-D(2): 163-173 (1995) - [j2]Ryotaro Kamimura, Shohachiro Nakanishi:
Kernel Hidden Unit Analysis-Network Size Reduction by Entropy Minimization-. IEICE Trans. Inf. Syst. 78-D(4): 484-489 (1995) - [j1]Ryotaro Kamimura, Shohachiro Nakanishi:
Feature detectors by autoencoders: Decomposition of input patterns into atomic features by neural networks. Neural Process. Lett. 2(6): 17-22 (1995) - [c10]Ryotaro Kamimura, Shohachiro Nakanishi:
Minimum α-information strategy for the interpretation of the network behaviors and the improved generalization. ICNN 1995: 974-978 - [c9]Ryotaro Kamimura, Shohachiro Nakanishi:
Information maximization for feature detection and pattern classification by autoencoders. ICNN 1995: 985-989 - [c8]Ryotaro Kamimura, Taeko Kamimura, Shohachiro Nakanishi:
Discovery of Linguistic Rules by Hidden Information Maximization. ICNN 1995: 2987-2991 - 1993
- [c7]Ryotaro Kamimura:
Minimum entropy methods in neural networks: competition and selective responses by entropy minimization. ICNN 1993: 219-225 - [c6]Ryotaro Kamimura:
Generation of Internal Representation by alpha. NIPS 1993: 271-278 - 1992
- [c5]Ryotaro Kamimura:
Competitive Learning by Entropy Minimization. ALT 1992: 111-122 - [c4]Ryotaro Kamimura:
Complexity Term to Generate Explicit Internal Representation in Recurrent Neural Networks. IFIP Congress (1) 1992: 336-342 - 1991
- [c3]Ryotaro Kamimura:
Application of the Recurrent Neural Network to the Problem of Language Acquisition. Conference on Analysis of Neural Network Applications 1991: 14-28 - 1990
- [c2]Ryotaro Kamimura:
Application of temporal supervised learning algorithm to generation of natural language. IJCNN 1990: 201-207 - [c1]Ryotaro Kamimura:
Recognition and restoration of periodic patterns with recurrent neural network. SPDP 1990: 436-440
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Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
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Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
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Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
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Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
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OpenAlex data
Load additional information about publications from 
.
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last updated on 2024-11-08 20:30 CET by the dblp team
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