Ryotaro Kamimura

ORCID

Publication Activity (10 Years)

Years Active: 1990-2023
Publications (10 Years): 47

Top Venues

Publications

Ryotaro Kamimura
Repeated Potentiality Augmentation for Multi-layered Neural Networks. FICC (2) (2023)
Ryotaro Kamimura
Destructive computing with winner-lose-all competition in multi-layered neural networks. Int. J. Hybrid Intell. Syst. 19 (3) (2023)
Ryotaro Kamimura
Contradiction neutralization for interpreting multi-layered neural networks. Appl. Intell. 53 (23) (2023)
Ryotaro Kamimura
Impartial competitive learning in multi-layered neural networks. Connect. Sci. 35 (1) (2023)
Ryotaro Kamimura, Ryozo Kitajima
Serially Disentangled Learning for Multi-Layered Neural Networks. IEA/AIE (2022)
Ryotaro Kamimura
Multi-level selective potentiality maximization for interpreting multi-layered neural networks. Appl. Intell. 52 (12) (2022)
Ryotaro Kamimura, Ryozo Kitajima
Min-Max Cost and Information Control in Multi-layered Neural Networks. FTC (1) (2022)
Ryotaro Kamimura
Cost-forced and repeated selective information minimization and maximization for multi-layered neural networks. Int. J. Hybrid Intell. Syst. 18 (1-2) (2022)
Ryotaro Kamimura
Cost-forced collective potentiality maximization by complementary potentiality minimization for interpreting multi-layered neural networks. Neurocomputing 480 (2022)
Ryotaro Kamimura
Selective Information Control and Layer-Wise Partial Collective Compression for Multi-Layered Neural Networks. ISDA (2021)
Ryotaro Kamimura
Selective Information Control and Network Compression in Multi-layered Neural Networks. IntelliSys (1) (2021)
Ryotaro Kamimura, Ryozo Kitajima
Forced Selective Information Reduction for Interpreting Multi-Layered Neural Networks. IIAI-AAI-Winter (2021)
Ryotaro Kamimura
Partially black-boxed collective interpretation and its application to SOM-based convolutional neural networks. Neurocomputing 450 (2021)
Ryotaro Kamimura
Minimum interpretation by autoencoder-based serial and enhanced mutual information production. Appl. Intell. 50 (8) (2020)
Ryotaro Kamimura
Disentangled Representations by Pseudo-Maximum Mutual Information for Interpreting Multi-Layered Neural Networks. IIAI-AAI (2020)
Ryotaro Kamimura
Cost-conscious mutual information maximization for improving collective interpretation of multi-layered neural networks. Neurocomputing 409 (2020)
Ryotaro Kamimura
Connective Potential Information for Collectively Interpreting Multi-Layered Neural Networks. SSCI (2020)
Ryotaro Kamimura
Compressing and Interpreting SOM-Based Convolutional Neural Networks. IEA/AIE (2020)
Ryotaro Kamimura
Cost-Conscious Internal Information Maximization for Disentangling and Interpreting Multi-layered Neural Networks. HIS (2020)
Ryotaro Kamimura
Bidirectional Estimation of Partially Black-Boxed Layers of SOM-Based Convolutional Neural Networks. IntelliSys (1) (2020)
Ryotaro Kamimura, Haruhiko Takeuchi
Improving collective interpretation by extended potentiality assimilation for multi-layered neural networks. Connect. Sci. 32 (2) (2020)
Ryotaro Kamimura
Mutual Information Generation for Improving Generalization and Interpretation in Neural Networks. IJCNN (2019)
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 (2019)
Ryotaro Kamimura
Supposed Maximum Mutual Information for Improving Generalization and Interpretation of Multi-Layered Neural Networks. J. Artif. Intell. Soft Comput. Res. 9 (2) (2019)
Ryotaro Kamimura, Haruhiko Takeuchi
Sparse semi-autoencoders to solve the vanishing information problem in multi-layered neural networks. Appl. Intell. 49 (7) (2019)
Ryotaro Kamimura
Neural self-compressor: Collective interpretation by compressing multi-layered neural networks into non-layered networks. Neurocomputing 323 (2019)
Ryotaro Kamimura
Interpreting Collectively Compressed Multi-Layered Neural Networks. CIS/RAM (2019)
Ryotaro Kamimura
Information Compression for Intelligible Multi-Layered Neural Networks. IIAI-AAI (2019)
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)
Ryotaro Kamimura
Autoeoncoders and Information Augmentation for Improved Generalization and Interpretation in Multi-layered Neural Networks. ISCBI (2018)
Ryotaro Kamimura, Haruhiko Takeuchi
Excessive, Selective and Collective Information Processing to Improve and Interpret Multi-layered Neural Networks. IntelliSys (1) (2018)
Ryotaro Kamimura
Information-Theoretic Self-compression of Multi-layered Neural Networks. TPNC (2018)
Ryotaro Kamimura, Haruhiko Takeuchi
Autoeconder-Based Excessive Information Generation for Improving and Interpreting Multi-layered Neural Networks. IIAI-AAI (2018)
Ryotaro Kamimura, Ryozo Kitajima, Hiroyuki Sakai
Local Selective Learning for Interpreting Multi-Layered Neural Networks. SCIS&ISIS (2018)
Ryotaro Kamimura, Haruhiko Takeuchi
Correlation-Constrained Mutual Information Maximization for Interpretable Multi-Layered Neural Networks. SCIS&ISIS (2018)
Ryotaro Kamimura, Tsubasa Kitago
Self-Assimilation for Solving Excessive Information Acquisition in Potential Learning. J. Artif. Intell. Soft Comput. Res. 8 (1) (2018)
Ryotaro Kamimura
Collective mutual information maximization to unify passive and positive approaches for improving interpretation and generalization. Neural Networks 90 (2017)
Ryotaro Kamimura
Potential layer-wise supervised learning for training multi-layered neural networks. IJCNN (2017)
Ryotaro Kamimura, Haruhiko Takeuchi
Supervised semi-autoencoder learning for multi-layered neural networks. IFSA-SCIS (2017)
Ryotaro Kamimura
Mutual information maximization for improving and interpreting multi-layered neural networks. SSCI (2017)
Ryotaro Kamimura
Direct Potentiality Assimilation for Improving Multi-Layered Neural Networks. FedCSIS (Position Papers) (2017)
Ryotaro Kamimura
Selective and cooperative potentiality maximization for improving interpretation and generalization. IJCNN (2017)
Ryotaro Kamimura
Simple and Stable Internal Representation by Potential Mutual Information Maximization. EANN (2016)
Ryotaro Kamimura
Repeated potentiality assimilation: Simplifying learning procedures by positive, independent and indirect operation for improving generalization and interpretation. IJCNN (2016)
Ryotaro Kamimura
Solving the Vanishing Information Problem with Repeated Potential Mutual Information Maximization. ICONIP (4) (2016)
Ryozo Kitajima, Ryotaro Kamimura, Osamu Uchida, Fujio Toriumi
Identifying Important Tweets by Considering the Potentiality of Neurons. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. (8) (2016)
Ryotaro Kamimura
Collective Interpretation and Potential Joint Information Maximization. Intelligent Information Processing (2016)
Ryotaro Kamimura
Simplified and gradual information control for improving generalization performance of multi-layered neural networks. IJCNN (2015)
Ryozo Kitajima, Ryotaro Kamimura, Osamu Uchida, Fujio Toriumi
Neural potential learning for tweets classification and interpretation. SoCPaR (2015)
Ryotaro Kamimura
Self-Organized Mutual Information Maximization Learning for Improved Generalization Performance. SMC (2015)
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) (2015)
Ryotaro Kamimura
Self-Organizing Selective Potentiality Learning to Detect Important Input Neurons. SMC (2015)
Ryotaro Kamimura, Ryozo Kitajima
Selective potentiality maximization for input neuron selection in self-organizing maps. IJCNN (2015)
Ryotaro Kamimura
Pseudo-potentiality maximization for improved interpretation and generalization in neural networks. IWCIA (2015)
Ryotaro Kamimura
Improving visualisation and prediction performance of supervised self-organising map by modified contradiction resolution. Connect. Sci. 27 (1) (2015)
Ryotaro Kamimura, Taeko Kamimura
Embedded information enhancement for neuron selection in self-organizing maps. SMC (2014)
Ryotaro Kamimura
Explicit knowledge extraction in information-theoretic supervised multi-layered SOM. FOCI (2014)
Ryotaro Kamimura
Information-theoretic multi-layered supervised self-organizing maps for improved prediction performance and explicit internal representation. SMC (2014)
Ryotaro Kamimura
Information acquisition performance by supervised information-theoretic self-organizing maps. NaBIC (2014)
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)
Ryotaro Kamimura
Input information maximization for improving self-organizing maps. Appl. Intell. 41 (2) (2014)
Ryotaro Kamimura
Contradiction resolution with explicit and limited evaluation and its application to SOM. IJCNN (2013)
Ryotaro Kamimura
Dependent input neuron selection in contradiction resolution. IWCIA (2013)
Ryotaro Kamimura
Controlling Relations between the Individuality and Collectivity of Neurons and its Application to Self-Organizing Maps. Neural Process. Lett. 38 (2) (2013)
Ryotaro Kamimura
Repeated comprehensibility maximization in competitive learning. Neural Comput. Appl. 22 (5) (2013)
Ryotaro Kamimura
Similarity interaction in information-theoretic self-organizing maps. Int. J. Gen. Syst. 42 (3) (2013)
Ryotaro Kamimura
Contradiction Resolution with Dependent Input Neuron Selection for Self-Organizing Maps. SMC (2013)
Ryotaro Kamimura
Comprehensibility maximization and humanly comprehensible representations. Int. J. Gen. Syst. 41 (3) (2012)
Ryotaro Kamimura
Relative information maximization and its application to the extraction of explicit class structure in SOM. Neurocomputing 82 (2012)
Ryotaro Kamimura
Interaction of individually and collectively treated neurons for explicit class structure in self-organizing maps. IJCNN (2012)
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) (2012)
Ryotaro Kamimura
Separation and Unification of Individuality and Collectivity and Its Application to Explicit Class Structure in Self-Organizing Maps. ICANN (2) (2012)
Ryotaro Kamimura
Contradiction Resolution for Foreign Exchange Rates Estimation. IJCCI (2012)
Ryotaro Kamimura
Contradiction resolution and its application to self-organizing maps. SMC (2012)
Ryotaro Kamimura
Relative Information Maximization and Its Application to the Detection of Explicit Class Structure in SOM. FOCI (2011)
Ryotaro Kamimura
Self-enhancement learning: target-creating learning and its application to self-organizing maps. Biol. Cybern. 104 (4-5) (2011)
Ryotaro Kamimura
Selective information enhancement learning for creating interpretable representations in competitive learning. Neural Networks 24 (4) (2011)
Ryotaro Kamimura
Explicit class structure with closeness and similarity between neurons. NaBIC (2011)
Ryotaro Kamimura
Explicit Class Structure by Weighted Cooperative Learning. ICANN (1) (2011)
Ryotaro Kamimura
Individually and Collectively Treated Neurons and its Application to SOM . IJCCI (NCTA) (2011)
Ryotaro Kamimura
Cooperation control and enhanced class structure in self-organizing maps. IJCNN (2011)
Ryotaro Kamimura
Structural enhanced information and its application to improved visualization of self-organizing maps. Appl. Intell. 34 (1) (2011)
Ryotaro Kamimura
Constrained information maximization by free energy minimization. Int. J. Gen. Syst. 40 (7) (2011)
Ryotaro Kamimura
Supposed maximum information for comprehensible representations in SOM. Neurocomputing 74 (7) (2011)
Ryotaro Kamimura
Pseudo-network Growing for Gradual Interpretation of Input Patterns. ICONIP (2) (2010)
Ryotaro Kamimura
Generation of Comprehensible Representations by Supposed Maximum Information. ICANN (2) (2010)
Ryotaro Kamimura
Explicit class structure produced by information-theoretic competitive and cooperative learning. NaBIC (2010)
Ryotaro Kamimura
Information enhancement for interpreting competitive learning. Int. J. Gen. Syst. 39 (7) (2010)
Ryotaro Kamimura
Information-theoretic enhancement learning and its application to visualization of self-organizing maps. Neurocomputing 73 (13-15) (2010)
Ryotaro Kamimura
Information-Theoretic Competitive and Cooperative Learning for Self-Organizing Maps. ICONIP (2) (2010)
Ryotaro Kamimura
Structural Enhanced Information to Detect Features in Competitive Learning. SMC (2009)
Ryotaro Kamimura
Selective enhancement learning in competitive learning. IJCNN (2009)
Ryotaro Kamimura
Self-enhancement learning: Self-supervised and target-creating learning. IJCNN (2009)
Ryotaro Kamimura
An information-theoretic approach to feature extraction in competitive learning. Neurocomputing 72 (10-12) (2009)
Ryotaro Kamimura
Enhancing and Relaxing Competitive Units for Feature Discovery. Neural Process. Lett. 30 (1) (2009)
Ryotaro Kamimura
Information Enhancement Learning: Local Enhanced Information to Detect the Importance of Input Variables in Competitive Learning. EANN (2009)
Ryotaro Kamimura
Relative Relaxation and Weighted Information Loss to Simplify and Stabilize Feature Detection. J. Adv. Comput. Intell. Intell. Informatics 13 (4) (2009)
Ryotaro Kamimura
Feature Discovery by Information Loss. J. Comput. 4 (10) (2009)
Ryotaro Kamimura
Self-supervised learning by information enhancement: Target-Generating and Spontaneous learning for Competitive Learning. SMC (2009)
Ryotaro Kamimura
Feature Detection by Structural Enhanced Information. ICONIP (2) (2008)

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Publication Activity (10 Years)

Top Topics

Top Venues

Ryotaro Kamimura