Ryotaro Kamimura

According to our database1, Ryotaro Kamimura authored at least 161 papers between 1990 and 2020.

Collaborative distances:
  • Dijkstra number2 of six.
  • Erdős number3 of five.

Timeline

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Bibliography

2020
Cost-conscious mutual information maximization for improving collective interpretation of multi-layered neural networks.
Neurocomputing, 2020

Improving collective interpretation by extended potentiality assimilation for multi-layered neural networks.
Connect. Sci., 2020

Minimum interpretation by autoencoder-based serial and enhanced mutual information production.
Appl. Intell., 2020

Compressing and Interpreting SOM-Based Convolutional Neural Networks.
Proceedings of the Trends in Artificial Intelligence Theory and Applications. Artificial Intelligence Practices, 2020

2019
Supposed Maximum Mutual Information for Improving Generalization and Interpretation of Multi-Layered Neural Networks.
J. Artif. Intell. Soft Comput. Res., 2019

Neural self-compressor: Collective interpretation by compressing multi-layered neural networks into non-layered networks.
Neurocomputing, 2019

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., 2019

Sparse semi-autoencoders to solve the vanishing information problem in multi-layered neural networks.
Appl. Intell., 2019

Interpreting Collectively Compressed Multi-Layered Neural Networks.
Proceedings of the 2019 IEEE International Conference on Cybernetics and Intelligent Systems (CIS) and IEEE Conference on Robotics, 2019

Mutual Information Generation for Improving Generalization and Interpretation in Neural Networks.
Proceedings of the International Joint Conference on Neural Networks, 2019

Relationship Between Management Policies and Profitability for Second Section-Listed Manufacturing Companies of the Tokyo Stock Exchange (2016 Results).
Proceedings of the 8th International Congress on Advanced Applied Informatics, 2019

Information Compression for Intelligible Multi-Layered Neural Networks.
Proceedings of the 8th International Congress on Advanced Applied Informatics, 2019

2018
Self-Assimilation for Solving Excessive Information Acquisition in Potential Learning.
J. Artif. Intell. Soft Comput. Res., 2018

Information-Theoretic Self-compression of Multi-layered Neural Networks.
Proceedings of the Theory and Practice of Natural Computing - 7th International Conference, 2018

Correlation-Constrained Mutual Information Maximization for Interpretable Multi-Layered Neural Networks.
Proceedings of the 2018 Joint 10th International Conference on Soft Computing and Intelligent Systems (SCIS) and 19th International Symposium on Advanced Intelligent Systems (ISIS), 2018

Local Selective Learning for Interpreting Multi-Layered Neural Networks.
Proceedings of the 2018 Joint 10th International Conference on Soft Computing and Intelligent Systems (SCIS) and 19th International Symposium on Advanced Intelligent Systems (ISIS), 2018

Autoeoncoders and Information Augmentation for Improved Generalization and Interpretation in Multi-layered Neural Networks.
Proceedings of the 6th International Symposium on Computational and Business Intelligence, 2018

Excessive, Selective and Collective Information Processing to Improve and Interpret Multi-layered Neural Networks.
Proceedings of the Intelligent Systems and Applications, 2018

Autoeconder-Based Excessive Information Generation for Improving and Interpreting Multi-layered Neural Networks.
Proceedings of the 7th International Congress on Advanced Applied Informatics, 2018

2017
Collective mutual information maximization to unify passive and positive approaches for improving interpretation and generalization.
Neural Networks, 2017

Mutual information maximization for improving and interpreting multi-layered neural networks.
Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence, 2017

Potential layer-wise supervised learning for training multi-layered neural networks.
Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

Selective and cooperative potentiality maximization for improving interpretation and generalization.
Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

Supervised semi-autoencoder learning for multi-layered neural networks.
Proceedings of the Joint 17th World Congress of International Fuzzy Systems Association and 9th International Conference on Soft Computing and Intelligent Systems, 2017

Direct Potentiality Assimilation for Improving Multi-Layered Neural Networks.
Proceedings of the Position Papers of the 2017 Federated Conference on Computer Science and Information Systems, 2017

2016
Identifying Important Tweets by Considering the Potentiality of Neurons.
IEICE Trans. Fundam. Electron. Commun. Comput. Sci., 2016

Repeated potentiality assimilation: Simplifying learning procedures by positive, independent and indirect operation for improving generalization and interpretation.
Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

Collective Interpretation and Potential Joint Information Maximization.
Proceedings of the Intelligent Information Processing VIII, 2016

Solving the Vanishing Information Problem with Repeated Potential Mutual Information Maximization.
Proceedings of the Neural Information Processing - 23rd International Conference, 2016

Simple and Stable Internal Representation by Potential Mutual Information Maximization.
Proceedings of the Engineering Applications of Neural Networks, 2016

2015
Accumulative Information Enhancement In The Self-Organizing Maps And Its Application To The Analysis Of Mission Statements.
J. Artif. Intell. Soft Comput. Res., 2015

Improving visualisation and prediction performance of supervised self-organising map by modified contradiction resolution.
Connect. Sci., 2015

Neural potential learning for tweets classification and interpretation.
Proceedings of the 7th International Conference of Soft Computing and Pattern Recognition, 2015

Self-Organizing Selective Potentiality Learning to Detect Important Input Neurons.
Proceedings of the 2015 IEEE International Conference on Systems, 2015

Self-Organized Mutual Information Maximization Learning for Improved Generalization Performance.
Proceedings of the 2015 IEEE International Conference on Systems, 2015

Selective potentiality maximization for input neuron selection in self-organizing maps.
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

Simplified and gradual information control for improving generalization performance of multi-layered neural networks.
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

Pseudo-potentiality maximization for improved interpretation and generalization in neural networks.
Proceedings of the IEEE 8th International Workshop on Computational Intelligence and Applications, 2015

2014
Input information maximization for improving self-organizing maps.
Appl. Intell., 2014

Embedded information enhancement for neuron selection in self-organizing maps.
Proceedings of the 2014 IEEE International Conference on Systems, Man, and Cybernetics, 2014

Information-theoretic multi-layered supervised self-organizing maps for improved prediction performance and explicit internal representation.
Proceedings of the 2014 IEEE International Conference on Systems, Man, and Cybernetics, 2014

Information acquisition performance by supervised information-theoretic self-organizing maps.
Proceedings of the 2014 Sixth World Congress on Nature and Biologically Inspired Computing, 2014

Explicit knowledge extraction in information-theoretic supervised multi-layered SOM.
Proceedings of the 2014 IEEE Symposium on Foundations of Computational Intelligence, 2014

Simplified Information Acquisition Method to Improve Prediction Performance: Direct Use of Hidden Neuron Outputs and Separation of Information Acquisition and Use Phase.
Proceedings of the International Workshop on Artificial Neural Networks and Intelligent Information Processing, 2014

2013
Controlling Relations between the Individuality and Collectivity of Neurons and its Application to Self-Organizing Maps.
Neural Process. Lett., 2013

Repeated comprehensibility maximization in competitive learning.
Neural Comput. Appl., 2013

Similarity interaction in information-theoretic self-organizing maps.
Int. J. Gen. Syst., 2013

Contradiction Resolution with Dependent Input Neuron Selection for Self-Organizing Maps.
Proceedings of the IEEE International Conference on Systems, 2013

Contradiction resolution with explicit and limited evaluation and its application to SOM.
Proceedings of the 2013 International Joint Conference on Neural Networks, 2013

Dependent input neuron selection in contradiction resolution.
Proceedings of the IEEE 6th International Workshop on Computational Intelligence and Applications, 2013

2012
Relative information maximization and its application to the extraction of explicit class structure in SOM.
Neurocomputing, 2012

Comprehensibility maximization and humanly comprehensible representations.
Int. J. Gen. Syst., 2012

Double enhancement learning for explicit internal representations: unifying self-enhancement and information enhancement to incorporate information on input variables.
Appl. Intell., 2012

Contradiction resolution and its application to self-organizing maps.
Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, 2012

Interaction of individually and collectively treated neurons for explicit class structure in self-organizing maps.
Proceedings of the 2012 International Joint Conference on Neural Networks (IJCNN), 2012

Contradiction Resolution for Foreign Exchange Rates Estimation.
Proceedings of the IJCCI 2012 - Proceedings of the 4th International Joint Conference on Computational Intelligence, Barcelona, Spain, 5, 2012

Separation and Unification of Individuality and Collectivity and Its Application to Explicit Class Structure in Self-Organizing Maps.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2012, 2012

2011
Selective information enhancement learning for creating interpretable representations in competitive learning.
Neural Networks, 2011

Supposed maximum information for comprehensible representations in SOM.
Neurocomputing, 2011

Constrained information maximization by free energy minimization.
Int. J. Gen. Syst., 2011

Self-enhancement learning: target-creating learning and its application to self-organizing maps.
Biol. Cybern., 2011

Structural enhanced information and its application to improved visualization of self-organizing maps.
Appl. Intell., 2011

Explicit class structure with closeness and similarity between neurons.
Proceedings of the Third World Congress on Nature & Biologically Inspired Computing, 2011

Cooperation control and enhanced class structure in self-organizing maps.
Proceedings of the 2011 International Joint Conference on Neural Networks, 2011

Individually and Collectively Treated Neurons and its Application to SOM .
Proceedings of the NCTA 2011, 2011

Explicit Class Structure by Weighted Cooperative Learning.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2011, 2011

Relative Information Maximization and Its Application to the Detection of Explicit Class Structure in SOM.
Proceedings of the IEEE Symposium on Foundations of Computational Intelligence, 2011

2010
Information-theoretic enhancement learning and its application to visualization of self-organizing maps.
Neurocomputing, 2010

Information enhancement for interpreting competitive learning.
Int. J. Gen. Syst., 2010

Explicit class structure produced by information-theoretic competitive and cooperative learning.
Proceedings of the Second World Congress on Nature & Biologically Inspired Computing, 2010

Information-Theoretic Competitive and Cooperative Learning for Self-Organizing Maps.
Proceedings of the Neural Information Processing. Models and Applications, 2010

Pseudo-network Growing for Gradual Interpretation of Input Patterns.
Proceedings of the Neural Information Processing. Models and Applications, 2010

Generation of Comprehensible Representations by Supposed Maximum Information.
Proceedings of the Artificial Neural Networks, 2010

2009
Enhancing and Relaxing Competitive Units for Feature Discovery.
Neural Process. Lett., 2009

Feature Discovery by Information Loss.
J. Comput., 2009

Relative Relaxation and Weighted Information Loss to Simplify and Stabilize Feature Detection.
J. Adv. Comput. Intell. Intell. Informatics, 2009

An information-theoretic approach to feature extraction in competitive learning.
Neurocomputing, 2009

Structural Enhanced Information to Detect Features in Competitive Learning.
Proceedings of the IEEE International Conference on Systems, 2009

Self-supervised learning by information enhancement: Target-Generating and Spontaneous learning for Competitive Learning.
Proceedings of the IEEE International Conference on Systems, 2009

Self-enhancement learning: Self-supervised and target-creating learning.
Proceedings of the International Joint Conference on Neural Networks, 2009

Selective enhancement learning in competitive learning.
Proceedings of the International Joint Conference on Neural Networks, 2009

Information Enhancement Learning: Local Enhanced Information to Detect the Importance of Input Variables in Competitive Learning.
Proceedings of the Engineering Applications of Neural Networks, 2009

2008
Mutual information maximization by free energy-based competitive learning for self-organizing maps.
Proceedings of the IEEE International Conference on Systems, 2008

Interpreting and improving multi-layered networks by free energy-based competitive learning.
Proceedings of the IEEE International Conference on Systems, 2008

Conditional information and information loss for flexible feature extraction.
Proceedings of the International Joint Conference on Neural Networks, 2008

Feature Discovery by Enhancement and Relaxation of Competitive Units.
Proceedings of the Intelligent Data Engineering and Automated Learning, 2008

Collective Activations to Generate Self-Organizing Maps.
Proceedings of the Advances in Neuro-Information Processing, 15th International Conference, 2008

Enhanced Visualization by Combing SOM and Mixture Models.
Proceedings of the Advances in Neuro-Information Processing, 15th International Conference, 2008

Feature Detection by Structural Enhanced Information.
Proceedings of the Advances in Neuro-Information Processing, 15th International Conference, 2008

Partially Enhanced Competitive Learning.
Proceedings of the Advances in Neuro-Information Processing, 15th International Conference, 2008

2007
Greedy network-growing algorithm with Minkowski distances.
Int. J. Gen. Syst., 2007

Information loss to extract distinctive features in competitive learning.
Proceedings of the IEEE International Conference on Systems, 2007

Forced Information Maximization to Accelerate Information-Theoretic Competitive Learning.
Proceedings of the International Joint Conference on Neural Networks, 2007

Controlled Competitive Learning: Extending Competitive Learning to Supervised Learning.
Proceedings of the International Joint Conference on Neural Networks, 2007

Partially Activated Neural Networks by Controlling Information.
Proceedings of the Artificial Neural Networks, 2007

Information-Theoretic Variable Selection in Neural Networks.
Proceedings of the IEEE Symposium on Foundations of Computational Intelligence, 2007

Forced Information and Information Loss for a Student Survey Analysis.
Proceedings of the IEEE Symposium on Foundations of Computational Intelligence, 2007

Combining Hard and Soft Competition in Information-Theoretic Learning.
Proceedings of the IEEE Symposium on Foundations of Computational Intelligence, 2007

Interpreting cabinet approval ratings by neural networks.
Proceedings of the IASTED International Conference on Artificial Intelligence and Applications, 2007

Forced information and information loss in information-theoretic competitive learning.
Proceedings of the IASTED International Conference on Artificial Intelligence and Applications, 2007

2006
Cooperative information maximization with Gaussian activation functions for self-organizing maps.
IEEE Trans. Neural Networks, 2006

Student Survey by Information-Theoretic Competitive Learning.
Proceedings of the IEEE International Conference on Systems, 2006

Controlling Excessive Information by Surface Information Criterion for Information-Theoretic Self-Organizing Maps.
Proceedings of the IEEE International Conference on Systems, 2006

Supervised Information Maximization by Weighted Distance.
Proceedings of the International Joint Conference on Neural Networks, 2006

Collective Information-Theoretic Competitive Learning: Emergency of Improved Performance by Collectively Treated Neurons.
Proceedings of the Neural Information Processing, 13th International Conference, 2006

Automatic Inference of Cabinet Approval Ratings by Information-Theoretic Competitive Learning.
Proceedings of the Neural Information Processing, 13th International Conference, 2006

Self-organizing by Information Maximization: Realizing Self-Organizing Maps by Information-Theoretic Competitive Learning.
Proceedings of the Neural Information Processing, 13th International Conference, 2006

2005
Unifying cost and information in information-theoretic competitive learning.
Neural Networks, 2005

Improving information-theoretic competitive learning by accentuated information maximization.
Int. J. Gen. Syst., 2005

Maximizing the Ratio of Information to Its Cost in Information Theoretic Competitive Learning.
Proceedings of the Artificial Neural Networks: Formal Models and Their Applications, 2005

Extracting Common and Distinctive Features by Cost-Sensitive Information Maximization.
Proceedings of the IASTED International Conference on Artificial Intelligence and Applications, 2005

Modular Structure Generation and Its Application to Feature Extraction.
Proceedings of the IASTED International Conference on Artificial Intelligence and Applications, 2005

2004
Cooperative information control for self-organizing maps.
Neurocomputing, 2004

Multi-Layered Greedy Network-Growing Algorithm: Extension of Greedy Network-Growing Algorithm to Multi-Layered Networks.
Int. J. Neural Syst., 2004

Improving feature extraction performance of greedy network-growing algorithm by inverse euclidean distance.
Connect. Sci., 2004

Cost-Sensitive Greedy Network-Growing Algorithm with Gaussian Activation Functions.
Proceedings of the Neural Information Processing, 11th International Conference, 2004

Teacher-Directed Learning with Gaussian and Sigmoid Activation Functions.
Proceedings of the Neural Information Processing, 11th International Conference, 2004

One-Epoch Learning for Supervised Information-Theoretic Competitive Learning.
Proceedings of the Neural Information Processing, 11th International Conference, 2004

2003
Information-Theoretic Competitive Learning with Inverse Euclidean Distance Output Units.
Neural Process. Lett., 2003

Teacher-directed learning: information-theoretic competitive learning in supervised multi-layered networks.
Connect. Sci., 2003

Information theoretic competitive learning in self-adaptive multi-layered networks.
Connect. Sci., 2003

Progressive Feature Extraction with a Greedy Network-growing Algorithm.
Complex Syst., 2003

Economic Data Analysis and Cooperative Information Control.
Proceedings of the IASTED International Conference on Modelling and Simulation (MS 2003), 2003

Information-theoretic Competitive Learning.
Proceedings of the IASTED International Conference on Modelling and Simulation (MS 2003), 2003

Improving Feature Extraction Performance of Greedy Network-Growing Algorithm.
Proceedings of the Intelligent Data Engineering and Automated Learning, 2003

Generating Explicit Self-Organizing Maps by Information Maximization.
Proceedings of the Intelligent Data Engineering and Automated Learning, 2003

Competitive Learning by Information Maximization: Eliminating Dead Neurons in Competitive Learning.
Proceedings of the Artificial Neural Networks and Neural Information Processing, 2003

2002
Controlling internal representations by structural information.
Neurocomputing, 2002

Greedy information acquisition algorithm: a new information theoretic approach to dynamic information acquisition in neural networks.
Connect. Sci., 2002

2001
Flexible feature discovery and structural information control.
Connect. Sci., 2001

Information Maximization and Language Acquisition.
Proceedings of the Artificial Neural Networks, 2001

Cooperative Information Control to Coordinate Competition and Cooperation.
Proceedings of the Artificial Neural Networks, 2001

2000
Information theoretic rule discovery in neural networks.
Proceedings of the IEEE International Conference on Systems, 2000

Selective Information Acquisition with Application to Pattern Classification.
Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, 2000

Conditional Information Analysis.
Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, 2000

1999
Controlling simple structural information to improve generalization performance.
Proceedings of the International Joint Conference Neural Networks, 1999

Mediated and multi-level information processing.
Proceedings of the International Joint Conference Neural Networks, 1999

1998
Minimizing alpha-Information for Generalization and Interpretation.
Algorithmica, 1998

Integrated Information Processors with Multi-functional Components.
Proceedings of the Fifth International Conference on Neural Information Processing, 1998

Structural Information Control to Improve Generalization.
Proceedings of the Fifth International Conference on Neural Information Processing, 1998

1997
Information Controller to Maximize and Minimize Information.
Neural Comput., 1997

Constrained Information Maximization to Control Internal Representatio.
J. Braz. Comput. Soc., 1997

Controlling α-entropy with a Neural α-Feature Detector.
Complex Syst., 1997

D-entropy controller for interpretation and generalization.
Proceedings of International Conference on Neural Networks (ICNN'97), 1997

D-entropy minimization: integration of mutual information maximization and minimization.
Proceedings of International Conference on Neural Networks (ICNN'97), 1997

1996
Unification of Information Maximization and Minimization.
Proceedings of the Advances in Neural Information Processing Systems 9, 1996

Kernel feature detector: extracting kernel features by minimizing /spl alpha/-information.
Proceedings of International Conference on Neural Networks (ICNN'96), 1996

Constrained information maximization.
Proceedings of International Conference on Neural Networks (ICNN'96), 1996

1995
Feature detectors by autoencoders: Decomposition of input patterns into atomic features by neural networks.
Neural Process. Lett., 1995

Improving Generalization Performance by Information Minimization.
IEICE Trans. Inf. Syst., 1995

Kernel Hidden Unit Analysis-Network Size Reduction by Entropy Minimization-.
IEICE Trans. Inf. Syst., 1995

Information maximization for feature detection and pattern classification by autoencoders.
Proceedings of International Conference on Neural Networks (ICNN'95), Perth, WA, Australia, November 27, 1995

Minimum /spl alpha/-information strategy for the interpretation of the network behaviors and the improved generalization.
Proceedings of International Conference on Neural Networks (ICNN'95), Perth, WA, Australia, November 27, 1995

Discovery of Linguistic Rules by Hidden Information Maximization.
Proceedings of International Conference on Neural Networks (ICNN'95), Perth, WA, Australia, November 27, 1995

1993
Generation of Internal Representation by alpha.
Proceedings of the Advances in Neural Information Processing Systems 6, 1993

Minimum entropy methods in neural networks: competition and selective responses by entropy minimization.
Proceedings of International Conference on Neural Networks (ICNN'88), San Francisco, CA, USA, March 28, 1993

1992
Complexity Term to Generate Explicit Internal Representation in Recurrent Neural Networks.
Proceedings of the Algorithms, Software, Architecture, 1992

Competitive Learning by Entropy Minimization.
Proceedings of the Algorithmic Learning Theory, Third Workshop, 1992

1991
Application of the Recurrent Neural Network to the Problem of Language Acquisition.
Proceedings of the Conference on Analysis of Neural Network Applications, 1991

1990
Recognition and restoration of periodic patterns with recurrent neural network.
Proceedings of the Second IEEE Symposium on Parallel and Distributed Processing, 1990

Application of temporal supervised learning algorithm to generation of natural language.
Proceedings of the IJCNN 1990, 1990


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