Ryotaro Kamimura

Ryotaro Kamimura, 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium.

Unification of Information Maximization and Minimization

Ryotaro Kamimura, 1996, NIPS.

Separation and Unification of Individuality and Collectivity and Its Application to Explicit Class Structure in Self-Organizing Maps

Ryotaro Kamimura, 2012, ICANN.

Mutual Information Generation for Improving Generalization and Interpretation in Neural Networks

Ryotaro Kamimura, R. Kamimura, 2019, 2019 International Joint Conference on Neural Networks (IJCNN).

Simplified and gradual information control for improving generalization performance of multi-layered neural networks

Ryotaro Kamimura, 2015, 2015 International Joint Conference on Neural Networks (IJCNN).

An information-theoretic approach to feature extraction in competitive learning

Ryotaro Kamimura, R. Kamimura, 2008, Neurocomputing.

Relative information maximization and its application to the extraction of explicit class structure in SOM

Ryotaro Kamimura, R. Kamimura, 2012, Neurocomputing.

Feature detectors by autoencoders: Decomposition of input patterns into atomic features by neural networks

Ryotaro Kamimura, Shohachiro Nakanishi, 2006, Neural Processing Letters.

Interpreting cabinet approval ratings by neural networks

Ryotaro Kamimura, Ryozo Kitajima, Fumihiko Yoshida, 2007, Artificial Intelligence and Applications.

Information Theoretic Competitive Learning and Linguistic Rule Acquisition

Ryotaro Kamimura, Thomas R. Shultz, Taeko Kamimura, 2001 .

Connective Potential Information for Collectively Interpreting Multi-Layered Neural Networks

Ryotaro Kamimura, 2020, 2020 IEEE Symposium Series on Computational Intelligence (SSCI).

Generating Explicit Self-Organizing Maps by Information Maximization

Ryotaro Kamimura, Haruhiko Takeuchi, 2003, IDEAL.

Complexity Term to Generate Explicit Internal Representation in Recurrent Neural Networks

Ryotaro Kamimura, 1992, IFIP Congress.

Improving generalization performance by information minimization

Ryotaro Kamimura, Shohachiro Nakanishi, Toshiyuki Takagi, 1994, Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94).

Information-Theoretic Variable Selection in Neural Networks

Ryotaro Kamimura, Ryozo Kitajima, Fumihiko Yoshida, 2007, 2007 IEEE Symposium on Foundations of Computational Intelligence.

Information-theoretic enhancement learning and its application to visualization of self-organizing maps

Ryotaro Kamimura, R. Kamimura, 2010, Neurocomputing.

Multi-Layered Greedy Network-Growing Algorithm: Extension of Greedy Network-Growing Algorithm to Multi-Layered Networks

Ryotaro Kamimura, 2004, Int. J. Neural Syst..

Controlling internal representations by structural information

Ryotaro Kamimura, R. Kamimura, 2002, Neurocomputing.

Controlling α-entropy with a Neural α-Feature Detector

Ryotaro Kamimura, R. Kamimura, 1997, Complex Syst..

Controlled Competitive Learning: Extending Competitive Learning to Supervised Learning

Ryotaro Kamimura, 2007, 2007 International Joint Conference on Neural Networks.

Competitive learning by mutual information maximization

Ryotaro Kamimura, T. Kamimura, R. Kamimura, 2001, IJCNN'01. International Joint Conference on Neural Networks. Proceedings (Cat. No.01CH37222).

Forced Information Maximization to Accelerate Information-Theoretic Competitive Learning

Ryotaro Kamimura, Ryozo Kitajima, 2007, 2007 International Joint Conference on Neural Networks.

Contradiction resolution and its application to self-organizing maps

Ryotaro Kamimura, R. Kamimura, 2012, 2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

Mediated and multi-level information processing

Ryotaro Kamimura, 1999, IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339).

Self-Organized Mutual Information Maximization Learning for Improved Generalization Performance

Ryotaro Kamimura, 2015, 2015 IEEE International Conference on Systems, Man, and Cybernetics.

Generation of Internal Representation by alpha

Ryotaro Kamimura, 1993, NIPS.

Contradiction resolution with explicit and limited evaluation and its application to SOM

Ryotaro Kamimura, R. Kamimura, 2013, The 2013 International Joint Conference on Neural Networks (IJCNN).

Generalization and C-information

Ryotaro Kamimura, S. Nakanishi, R. Kamimura, 1994, Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94).

Partially Enhanced Competitive Learning

Ryotaro Kamimura, 2008, ICONIP.

Cooperative Information Control for Self-Organizing Maps

Ryotaro Kamimura, R. Kamimura, 2002, Neurocomputing.

Minimum Information Principle in Neural Networks : Information in Hidden Units and Generalization Performance

Ryotaro Kamimura, Shohachiro Nakanishi, 1994 .

Collective mutual information maximization to unify passive and positive approaches for improving interpretation and generalization

Ryotaro Kamimura, R. Kamimura, 2017, Neural Networks.

Relative Relaxation and Weighted Information Loss to Simplify and Stabilize Feature Detection

Ryotaro Kamimura, 2009, J. Adv. Comput. Intell. Intell. Informatics.

Embedded information enhancement for neuron selection in self-organizing maps

Ryotaro Kamimura, Taeko Kamimura, 2014, 2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

Information-Theoretic Self-compression of Multi-layered Neural Networks

Ryotaro Kamimura, R. Kamimura, 2018, TPNC.

Neural self-compressor: Collective interpretation by compressing multi-layered neural networks into non-layered networks

Ryotaro Kamimura, R. Kamimura, 2019, Neurocomputing.

Explicit knowledge extraction in information-theoretic supervised multi-layered SOM

Ryotaro Kamimura, R. Kamimura, 2014, 2014 IEEE Symposium on Foundations of Computational Intelligence (FOCI).

Simple and Stable Internal Representation by Potential Mutual Information Maximization

Ryotaro Kamimura, R. Kamimura, 2016, EANN.

Controlling Relations between the Individuality and Collectivity of Neurons and its Application to Self-Organizing Maps

Ryotaro Kamimura, R. Kamimura, 2012, Neural Processing Letters.

Competitive Learning by Information Maximization: Eliminating Dead Neurons in Competitive Learning

Ryotaro Kamimura, 2003, ICANN.

Maximizing the Ratio of Information to Its Cost in Information Theoretic Competitive Learning

Ryotaro Kamimura, Sachiko Aida-Hyugaji, 2005, ICANN.

Information-Theoretic Competitive Learning with Inverse Euclidean Distance Output Units

Ryotaro Kamimura, R. Kamimura, 2003, Neural Processing Letters.

Cooperative Information Control to Coordinate Competition and Cooperation

Ryotaro Kamimura, Taeko Kamimura, 2001, ICANN.

Self-supervised learning by information enhancement: Target-generating and spontaneous learning for competitive learning

Ryotaro Kamimura, R. Kamimura, 2009, 2009 IEEE International Conference on Systems, Man and Cybernetics.

Cooperative information control for self-organization maps

Ryotaro Kamimura, tTaeko Kamimura, 2001, IJCNN'01. International Joint Conference on Neural Networks. Proceedings (Cat. No.01CH37222).

Self-Assimilation for Solving Excessive Information Acquisition in Potential Learning

Ryotaro Kamimura, Tsubasa Kitago, R. Kamimura, 2018, J. Artif. Intell. Soft Comput. Res..

Selective potentiality maximization for input neuron selection in self-organizing maps

Ryotaro Kamimura, Ryozo Kitajima, 2015, 2015 International Joint Conference on Neural Networks (IJCNN).

Structural enhanced information to detect features in competitive learning

Ryotaro Kamimura, 2009, 2009 IEEE International Conference on Systems, Man and Cybernetics.

Conditional information and information loss for flexible feature extraction

Ryotaro Kamimura, R. Kamimura, 2008, 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence).

Constrained information maximization by free energy minimization

Ryotaro Kamimura, R. Kamimura, 2011, Int. J. Gen. Syst..

Constrained information maximization

Ryotaro Kamimura, S. Nakanishi, 1996, Proceedings of International Conference on Neural Networks (ICNN'96).

Supervised Information Maximization by Weighted Distance

Ryotaro Kamimura, 2006, The 2006 IEEE International Joint Conference on Neural Network Proceedings.

Improving visualisation and prediction performance of supervised self-organising map by modified contradiction resolution

Ryotaro Kamimura, R. Kamimura, 2015, Connect. Sci..

Autoeoncoders and Information Augmentation for Improved Generalization and Interpretation in Multi-layered Neural Networks

Ryotaro Kamimura, 2018, 2018 6th International Symposium on Computational and Business Intelligence (ISCBI).

Feature Detection by Structural Enhanced Information

Ryotaro Kamimura, 2008, ICONIP.

Collective Information-Theoretic Competitive Learning: Emergency of Improved Performance by Collectively Treated Neurons

Ryotaro Kamimura, Ryozo Kitajima, Fumihiko Yoshida, 2006, ICONIP.

Constrained Information Maximization to Control Internal Representatio

Ryotaro Kamimura, 1997, J. Braz. Comput. Soc..

Teacher-Directed Learning with Gaussian and Sigmoid Activation Functions

Ryotaro Kamimura, R. Kamimura, 2004, ICONIP.

Integrated Information Processors with Multi-functional Components

Ryotaro Kamimura, 1998, ICONIP.

Combining Hard and Soft Competition in Information-Theoretic Learning

Ryotaro Kamimura, 2007, 2007 IEEE Symposium on Foundations of Computational Intelligence.

Neural potential learning for tweets classification and interpretation

Ryotaro Kamimura, Ryozo Kitajima, Fujio Toriumi, 2015, 2015 7th International Conference of Soft Computing and Pattern Recognition (SoCPaR).

Learning by /spl alpha/-divergence

Ryotaro Kamimura, Shohachiro Nakanishi, 1995, Proceedings of 1995 IEEE International Conference on Fuzzy Systems..

Free energy-based competitive learning and minimum information production learning

Ryotaro Kamimura, 2008 .

Information enhancement for interpreting competitive learning

Ryotaro Kamimura, R. Kamimura, 2010, Int. J. Gen. Syst..

Improving generalization performance by controlling /spl alpha/-information

Ryotaro Kamimura, S. Nakanishi, 1994, Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94).

Teacher-directed learning: information-theoretic competitive learning in supervised multi-layered networks

Ryotaro Kamimura, Fumihiko Yoshida, R. Kamimura, 2003, Connect. Sci..

Selective information enhancement learning for creating interpretable representations in competitive learning

Ryotaro Kamimura, R. Kamimura, 2011, Neural Networks.

Accumulative Information Enhancement In The Self-Organizing Maps And Its Application To The Analysis Of Mission Statements

Ryotaro Kamimura, Ryozo Kitajima, 2015, J. Artif. Intell. Soft Comput. Res..

Simplified Information Acquisition Method to Improve Prediction Performance: Direct Use of Hidden Neuron Outputs and Separation of Information Acquisition and Use Phase

Ryotaro Kamimura, 2014, ANNIIP.

One-Epoch Learning for Supervised Information-Theoretic Competitive Learning

Ryotaro Kamimura, 2004, ICONIP.

Direct Potentiality Assimilation for Improving Multi-Layered Neural Networks

Ryotaro Kamimura, 2017, FedCSIS.

Repeated potentiality assimilation: Simplifying learning procedures by positive, independent and indirect operation for improving generalization and interpretation

Ryotaro Kamimura, 2016, 2016 International Joint Conference on Neural Networks (IJCNN).

Comprehensibility maximization and humanly comprehensible representations

Ryotaro Kamimura, R. Kamimura, 2012, Int. J. Gen. Syst..

Contradiction Resolution for Foreign Exchange Rates Estimation

Ryotaro Kamimura, R. Kamimura, 2012, IJCCI.

Interpreting and improving multi-layered networks by free energy-based competitive learning

Ryotaro Kamimura, 2008, 2008 IEEE International Conference on Systems, Man and Cybernetics.

Self-enhancement learning: Self-supervised and target-creating learning

Ryotaro Kamimura, R. Kamimura, 2009, 2009 International Joint Conference on Neural Networks.

Repeated comprehensibility maximization in competitive learning

Ryotaro Kamimura, R. Kamimura, 2013, Neural Computing and Applications.

Information Maximization and Language Acquisition

Ryotaro Kamimura, Taeko Kamimura, R. Kamimura, 2001, ICANN.

Greedy information acquisition algorithm: A new information theoretic approach to dynamic information acquisition in neural networks

Ryotaro Kamimura, Haruhiko Takeuchi, Taeko Kamimura, 2002, Connect. Sci..

Minimum entropy methods in neural networks: competition and selective responses by entropy minimization

Ryotaro Kamimura, 1993, IEEE International Conference on Neural Networks.

Extracting Common and Distinctive Features by Cost-Sensitive Information Maximization

Ryotaro Kamimura, 2005, Artificial Intelligence and Applications.

Improving collective interpretation by extended potentiality assimilation for multi-layered neural networks

Ryotaro Kamimura, Haruhiko Takeuchi, R. Kamimura, 2020, Connect. Sci..

Controlling Excessive Information by Surface Information Criterion for Information-Theoretic Self-Organizing Maps

Ryotaro Kamimura, 2006, 2006 IEEE International Conference on Systems, Man and Cybernetics.

Supervised semi-autoencoder learning for multi-layered neural networks

Ryotaro Kamimura, Haruhiko Takeuchi, R. Kamimura, 2017, 2017 Joint 17th World Congress of International Fuzzy Systems Association and 9th International Conference on Soft Computing and Intelligent Systems (IFSA-SCIS).

Recurrent neural network to acquire the grammatical competence

Ryotaro Kamimura, R. Kamimura, 1991, IJCNN-91-Seattle International Joint Conference on Neural Networks.

Dependent input neuron selection in contradiction resolution

Ryotaro Kamimura, R. Kamimura, 2013, 2013 IEEE 6th International Workshop on Computational Intelligence and Applications (IWCIA).

Local Selective Learning for Interpreting Multi-Layered Neural Networks

Ryotaro Kamimura, Hiroyuki Sakai, Ryozo Kitajima, 2018, 2018 Joint 10th International Conference on Soft Computing and Intelligent Systems (SCIS) and 19th International Symposium on Advanced Intelligent Systems (ISIS).

Collective Interpretation and Potential Joint Information Maximization

Ryotaro Kamimura, R. Kamimura, 2016, Intelligent Information Processing.

Greedy network-growing algorithm with Minkowski distances

Ryotaro Kamimura, Osamu Uchida, Seiki Hashimoto, 2007, Int. J. Gen. Syst..

Combining forward and backward WTA for partially activated neural networks

Ryotaro Kamimura, 2007 .

Automatic Inference of Cabinet Approval Ratings by Information-Theoretic Competitive Learning

Ryotaro Kamimura, Fumihiko Yoshida, 2006, ICONIP.

Individually and Collectively Treated Neurons and its Application to SOM

Ryotaro Kamimura, R. Kamimura, 2011, IJCCI.

SOM Knowledge Induced Learning with Maximum Information Principle to Improve Multi-Layered Neural Networks

Ryotaro Kamimura, Ryozo Kitajima, 2015 .

Input information maximization for improving self-organizing maps

Ryotaro Kamimura, R. Kamimura, 2014, Applied Intelligence.

Cooperation control and enhanced class structure in self-organizing maps

Ryotaro Kamimura, R. Kamimura, 2011, The 2011 International Joint Conference on Neural Networks.

Collective Activations to Generate Self-Organizing Maps

Ryotaro Kamimura, 2008, ICONIP.

Identifying Important Tweets by Considering the Potentiality of Neurons

Ryotaro Kamimura, Ryozo Kitajima, Fujio Toriumi, 2016, IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences.

Correlation-Constrained Mutual Information Maximization for Interpretable Multi-Layered Neural Networks

Ryotaro Kamimura, Haruhiko Takeuchi, 2018, 2018 Joint 10th International Conference on Soft Computing and Intelligent Systems (SCIS) and 19th International Symposium on Advanced Intelligent Systems (ISIS).

Minimum interpretation by autoencoder-based serial and enhanced mutual information production

Ryotaro Kamimura, 2020, Applied Intelligence.

Pseudo-potentiality maximization for improved interpretation and generalization in neural networks

Ryotaro Kamimura, 2015, 2015 IEEE 8th International Workshop on Computational Intelligence and Applications (IWCIA).

Explicit class structure with closeness and similarity between neurons

Ryotaro Kamimura, R. Kamimura, 2011, 2011 Third World Congress on Nature and Biologically Inspired Computing.

Selective and cooperative potentiality maximization for improving interpretation and generalization

Ryotaro Kamimura, R. Kamimura, 2017, 2017 International Joint Conference on Neural Networks (IJCNN).

Selective information acquisition with application to pattern classification

Ryotaro Kamimura, 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium.

Kernel Hidden Unit Analysis-Network Size Reduction by Entropy Minimization-

Ryotaro Kamimura, Shohachiro Nakanishi, Shohachiro Nakanishi, 1995, IEICE Trans. Inf. Syst..

Application of the recurrent neural network to the problem of language acquisition

Ryotaro Kamimura, R. Kamimura, 1991, ANNA '91.

Self-enhancement learning: target-creating learning and its application to self-organizing maps

Ryotaro Kamimura, R. Kamimura, 2011, Biological Cybernetics.

Improving Feature Extraction Performance of Greedy Network-Growing Algorithm

Ryotaro Kamimura, Osamu Uchida, 2003, IDEAL.

Information acquisition performance by supervised information-theoretic self-organizing maps

Ryotaro Kamimura, 2014, 2014 Sixth World Congress on Nature and Biologically Inspired Computing (NaBIC 2014).

Excessive, Selective and Collective Information Processing to Improve and Interpret Multi-layered Neural Networks

Ryotaro Kamimura, Haruhiko Takeuchi, 2018, IntelliSys.

Partially Activated Neural Networks by Controlling Information

Ryotaro Kamimura, 2007, ICANN.

SOM-based information maximization to improve and interpret multi-layered neural networks: From information reduction to information augmentation approach to create new information

Ryotaro Kamimura, R. Kamimura, 2019, Expert Syst. Appl..

Enhanced Visualization by Combing SOM and Mixture Models

Ryotaro Kamimura, 2008, ICONIP.

Sparse semi-autoencoders to solve the vanishing information problem in multi-layered neural networks

Ryotaro Kamimura, Haruhiko Takeuchi, R. Kamimura, 2019, Applied Intelligence.

Ryotaro Kamimura, R. Kamimura, 2013, Int. J. Gen. Syst..

Improving feature extraction performance of greedy network-growing algorithm by inverse euclidean distance

Ryotaro Kamimura, 2004, Connect. Sci..

Student Survey byInformation-Theo retic Competitive Learning

Ryotaro Kamimura, 2006 .

Structural Information Control to Improve Generalization

Ryotaro Kamimura, 1998, ICONIP.

Information-Theoretic Competitive and Cooperative Learning for Self-Organizing Maps

Ryotaro Kamimura, 2010, ICONIP.

Flexible feature discovery and structural information control

Ryotaro Kamimura, Osamu Uchida, Taeko Kamimura, 2001, Connect. Sci..

Information theoretic competitive learning in self-adaptive multi-layered networks

Ryotaro Kamimura, R. Kamimura, 2003, Connect. Sci..

2014 IEEE Symposium on Foundations of Computational Intelligence, FOCI 2014, Orlando, FL, USA, December 9-12, 2014

Ryotaro Kamimura, Upul Senanayake, Mahendra Piraveenan, 2014, FOCI.

Self-Organizing Selective Potentiality Learning to Detect Important Input Neurons

Ryotaro Kamimura, 2015, 2015 IEEE International Conference on Systems, Man, and Cybernetics.

Interaction of individually and collectively treated neurons for explicit class structure in self-organizing maps

Ryotaro Kamimura, R. Kamimura, 2012, The 2012 International Joint Conference on Neural Networks (IJCNN).

Information Controller to Maximize and Minimize Information

Ryotaro Kamimura, 1997, Neural Computation.

Potential layer-wise supervised learning for training multi-layered neural networks

Ryotaro Kamimura, R. Kamimura, 2017, 2017 International Joint Conference on Neural Networks (IJCNN).

Cooperation-Controlled Learning for Explicit Class Structure in Self-Organizing Maps

Ryotaro Kamimura, R. Kamimura, 2014, TheScientificWorldJournal.

Inference of Cabinet approval ratings by neural networks

Ryotaro Kamimura, Ryozo Kitajima, Fumihiko Yoshida, 2006 .

Mutual information maximization by free energy-based competitive learning for self-organizing maps

Ryotaro Kamimura, R. Kamimura, 2008, 2008 IEEE International Conference on Systems, Man and Cybernetics.

Forced information and information loss in information-theoretic competitive learning

Ryotaro Kamimura, 2007, Artificial Intelligence and Applications.

Pseudo-network Growing for Gradual Interpretation of Input Patterns

Ryotaro Kamimura, 2010, ICONIP.

Information loss to extract distinctive features in competitive learning

Ryotaro Kamimura, R. Kamimura, 2007, 2007 IEEE International Conference on Systems, Man and Cybernetics.

Selective Information Control and Network Compression in Multi-layered Neural Networks

Ryotaro Kamimura, R. Kamimura, 2021, IntelliSys.

Partially black-boxed collective interpretation and its application to SOM-based convolutional neural networks

Ryotaro Kamimura, R. Kamimura, 2021, Neurocomputing.

Controlling Potential Information to Unify Internal Structure for Improved Interpretation and Generalization in Multi-layered Neural Networks

Ryotaro Kamimura, R. Kamimura, 2021 .

Simplifying Potential Learning by Supposing Maximum and Minimum Information for Improved Generalization and Interpretation

Ryotaro Kamimura, Ryozo Kitajima, R. Kamimura, 2016 .

Generation of Internal Representation by α-Transformation

Ryotaro Kamimura, 1993, NIPS 1993.

Generation of Inhibitory Connections to Minimize Internal and External Entropy

Ryotaro Kamimura, 1992 .

Internal representation with minimum entropy in recurrent neural networks: minimizing entropy through inhibitory connections

Ryotaro Kamimura, R. Kamimura, 1993 .

A Stepwise AIC Method for Variable Selection in Linear Regression

Ryotaro Kamimura, R. Kamimura, Toshie Yamashita, 2007 .