Kyushu University Academic Staff Educational and Research Activities Database
Researcher information (To researchers) Need Help? How to update
Jun'ichi Takeuchi Last modified date:2016.09.27



Graduate School
Undergraduate School


Homepage
http://www.me.inf.kyushu-u.ac.jp/en/member.html
Academic Degree
Dr.Eng
Field of Specialization
Learning Theory, Information Theory, Machine Learning
Research
Research Interests
  • Information-Based Induction Sciences and its Application
    keyword : Learning Theory, Information Theory, Stochastic Complexity, Information Geometry, Machine Learning, Super Resulution, Network Security
    2006.04.
Academic Activities
Books
1. Jun'ichi Takeuchi, ``An introduction of the minimum description length principle.''
(A chapter of ``A Mathematical Approach to Research Problems of Science and Technology,'' pp. 279-296,
Ryuei Nishii, Shin-ichiro Ei, Miyuki Koiso, Hiroyuki Ochiai, Kanzoh Okada, Shingo Saito, Tomoyuki Shira (editors))
, Springer, 2014.07.
Papers
1. Yoshinari Takeishi, Masanori Kawakita, Jun'ichi Takeuchi, Least Squares Superposition Codes with Bernoulli Dictionary are Still Reliable at Rates up to Capacity, IEEE Transactions on Information Theory, 60, 5, 2014.05.
2. Jun'ichi Takeuchi, Tsutomu Kawabata, Andrew R. Barron, Properties of Jeffreys mixture of Markov Sources, IEEE transactions on Information Theory, 59, 1, 2013.01.
3. J. Takeuchi & K. Yamanishi, A Unifying Framework for Detecting Outliers and Change Points from Non-Stationary Time Series Data, IEEE transactions on Knowledge and Data Engineering, Vol. 18, No. 4, pp.482-489, 2006.04.
4. J. Takeuchi & S. Amari, α-Parallel Prior and Its Properties, IEEE transactions on Information Theory, Vol. 51, No. 3, pp. 1011-1023, 2005.03.
5. K. Yamanishi, J. Takeuchi, G. Williamas, & P. Milne, On-line Unsupervised Oultlier Detection Using Finite Mixtures with Discounting Learning Algorithms, Data Mining and Knowleged Discovery Journal, 8 (3): 275-300, 2004.05.
6. J. Takeuchi, N. Abe, & S. Amari, The Lob-Pass problem, Journal of Computer and System Sciences, 2000.03.
7. J. Takeuchi, Characterization of the Bayes estimator and the MDL estimator for exponential families, IEEE transactions on Information Theory, Vol. 43, No. 4, pp. 1165-1174, 1997, 1997.01.
Presentations
1. Yoshinari Takeishi, Jun'ichi Takeuchi, An Improved Upper Bound on Block Error Probability of Least Squares Superposition Codes with Unbiased Bernoulli Dictionary, 2016 IEEE International Symposium on Information Theory, 2016.07.10.
2. Masanori Kawakita, Jun'ichi Takeuchi, Barron and Cover's Theory in Supervised Learning and Its Application to Lasso, The 33rd International Conference on Machine Learning, 2016.06.19.
3. Jun'ichi Takeuchi, Andrew R. Barron, Stochastic complexity for tree models, 2014 IEEE Information Theory Workshop, 2014.11.03.
4. Jun'ichi Takeuchi, Andrew R. Barron, Asymptotically minimax regret for models with hidden variables, 2014 IEEE International Symposium on Information Theory, 2014.07.04.
5. Jun'ichi Takeuchi, Andrew R. Barron, Asymptotically Minimax Regret by Bayes Mixtures for Non-exponential Families, 2013 IEEE Information Theory Workshop, 2013.09.10.
6. Yoshinari Takeishi, Masanori Kawakita, Jun'ichi Takeuchi, Least Squares Superposition Codes with Bernoulli Dictionary are Still Reliable at Rates up to Capacity, 2013 IEEE International Symposium on Information Theory, 2013.07.09.
7. Sayaka Yamauchi, Masanori Kawakita, Jun'ichi Takeuchi, Botnet Detection based on Non-negative Matrix Factorization and the MDL Principle, the 19th International Conference on Neural Information Processing, 2012.11.14.
8. Kotaro Yamaguchi, Masanori Kawakita, Norikazu Takahashi, Jun'ichi Takeuchi, Information Theoretic Limit of Single Frame Superresolution, The Third International Conference on Emerging Security Technologies, 2012.09.05.
9. Jun'ichi Takeuchi, Yoshinari Takeishi, Sparse Superposition Codes with Discrete Dictionary, The 5th Workshop on Information Theoretic Methods in Science and Engineering, 2012.08.30.
10. Mariko Tsurusaki, Jun'ichi Takeuchi, Constant Markov Portfolio and Its Application to Universal Portfolio with Side Information, 2012 IEEE International Symposium on Information Theory, 2012.07.04.