Ryozo Kitajima

According to our database1, Ryozo Kitajima authored at least 14 papers between 2006 and 2022.

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

Timeline

Legend:

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Links

On csauthors.net:

Bibliography

2022
Serially Disentangled Learning for Multi-Layered Neural Networks.
Proceedings of the Advances and Trends in Artificial Intelligence. Theory and Practices in Artificial Intelligence, 2022

Min-Max Cost and Information Control in Multi-layered Neural Networks.
Proceedings of the Future Technologies Conference, 2022

2020
What Do Good Integrated Reports Tell Us?: An Empirical Study of Japanese Companies Using Text-Mining.
Proceedings of the 9th International Congress on Advanced Applied Informatics, 2020

2019
Extraction of Characteristic Terms from Patent Documents for Technical Trend Analysis.
Proceedings of the 8th International Congress on Advanced Applied Informatics, 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

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

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

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

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

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

Information-Theoretic Variable Selection in Neural Networks.
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

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


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