| Kohei Hatano | Last modified date：2024.04.10 |
Professor /
Department of Informatics /
Faculty of Information Science and Electrical Engineering
Presentations
| 1. | Kohei Hatano, Blackwell game and its applications in online prediction tasks, Forum "Math-for-Industry" 2021, 2021.12. |
| 2. | Yaxiong Liu, Kohei Hatano, and Eiji Takimoto, Improved Algorithms for Online Load Balancing, 情報処理学会 第174回アルゴリズム研究会, 2019.09. |
| 3. | Daiki Suehiro, Kohei Hatano, Eiji Takimoto, Shuji Yamamoto, Kenichi Bannai and Akiko Takeda, Learning theory and algorithms for shapelets and other local features, NIPS 2017 Time Series Workshop, 2017.12. |
| 4. | , [URL]. |
| 5. | Kengo Kuwahara, 末廣 大貴, 畑埜 晃平, 瀧本 英二, D. Suehiro, K. Kuwahara, K. Hatano, E. Takimoto, “Time Series Classification Based on Rom Shapelets,” , 2016., NIPS 2016 Time Series Workshop, 2016.12. |
| 6. | Takahiro Fujita, Kohei Hatano, Shuji Kijima, Eiji Takimoto, Online Linear Optimization over Permutations with Precedence Constraints , NIPS 2014 Workshop on Discrete Optimization in Machine Learning(DISCML), 2014.12. |
| 7. | Issei Matsumoto, Kohei Hatano, Eiji Takimoto, Online Prediction with Bradley-Terry Models, NIPS 2014 Workshop on Analysis of Rank Data: Confluence of Social Choice, Operations Research, and Machine Learning, 2014.12. |
| 8. | Combinatorial MTS problem. |
| 9. | Online scheduling of precedence-constrained jobs on a single machine. |
| 10. | 畑埜 晃平, Combinatorial Online Prediction via Metarounding, TCE Guest Lecture, 2013.12. |
| 11. | Takahiro Fujita, Kohei Hatano, Eiji Takimoto, Combinatorial Online Prediction Using Offline Approximation Algorithms, The sixth Annual Meeting of Asian Association for Algorithms and Computation (AAAC2013), 2013.04. |
| 12. | Daiki Suehiro, Kohei Hatano, Shuji Kijima, Eiji Takimoto, Kiyohito Nagano, Online Prediction over Base Polyhedra , NIPS 2012 Workshop on Discrete Optimization in Machine Learning(DISCML), 2012.12. |
| 13. | Online Rank Aggregation. |
| 14. | Online Rank Aggregation. |
| 15. | Learning evaluation functions for Shogi via bipertite ranking learning with SVMs . |
| 16. | Learning evaluation functions for Shogi via bipertite ranking learning with SVMs . |
| 17. | Online Rank Aggregation. |
| 18. | Online Rank Aggregation. |
| 19. | Online Learning Based On Maximum Entropy Principle. |
| 20. | Online Learning of Maximum p-Norm Margin Classifiers with Bias. |
| 21. | Efficient online learning of linear threshold functions with large biases.. |
| 22. | Boosting using classifiers with nearly one-sided error. |
| 23. | An Efficient Boosting by Filtering. |
| 24. | Boosting by filtering using an information-theoretic criterion. |
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