Achievement System - KITAJIMA Ryozo | Tokyo Polytechnic University

（Last updated : 2024-09-19 13:17:20）

KITAJIMA Ryozo

Department / Course Tokyo Polytechnic University Faculty of Engineering Department of Engineering

Job Assistant Professor

Academic background
2013/04～2017/03	Doctorial Graduate School of Science and Technology, Tokai University Finished
2002/04～2006/03	TOKAI UNIVERSITY Graduated

Business career
2017/09/15 ～ 2019/09/30	Research associate
2019/10/01 ～	Assistant Professor Tokyo Polytechnic University Faculty of Engineering Department of Engineering

Present specialized field
Others, Intelligent informatics

Book and thesis
Papers	Accumulative Informa- tion Enhancement in the Self-Organizing Maps and Its Application to the Analysis of Mission Statements Journal of Artificial Intelligence and Soft Computing Research 5 (3),pp.161-176 (Co-authored) 2015/04/01
Papers	Neural Potential Learning for Tweets Classification and Interpretation,pp.141-148 (Co-authored) 2015/04/01
Papers	Potential Information Maximization: Potentiality-Driven Information Maximization and Its Application to Tweets Classification and Interpretation The International Journal of Computer In- formation Systems and Industrial Management Applications 8,pp.42-51 (Co-authored) 2016/04/01
Papers	Identifying Important Tweets by Considering the Potentiality of Neurons E99A (8),pp.1555-1559 (Co-authored) 2016/08/01
Papers	Examination of social media guidelines at universities in Japan using an artificial neural network,pp.283-288 (Co-authored) 2017/04/01
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Academic conference presentation
2023/08/02	Revealing the relationship between transpolar arc occurrence and solar wind conditions using the novel neural network (Potential Learning): Initial Results (20th Asia Oceania Geosciences Society Annual Meeting)
2023/02/24	A Sentiment Analysis of Data on Outings from Mothers with Infants and Toddlers during the COVID-19 Pandemic (The 6th International Conference on Data Storage and Data Engineering (DSDE 2023))
2022/10/20	Min-Max Cost and Information Control in Multi-Layered Neural Networks (Future Technologies Conference 2022 (FTC 2022))
2016/06/15	Neural potential learning for tweets classification and interpretation
2016/04/01	Simplifying potential learning by supposing maximum and minimum information for improved generalization and interpretation
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Department laboratory expense researcher number
50815545