Kyushu University Academic Staff Educational and Research Activities Database
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Jun'ichi Takeuchi Last modified date:2020.07.01



Graduate School
Undergraduate School
Other Organization


Homepage
https://kyushu-u.pure.elsevier.com/en/persons/junnichi-takeuchi
 Reseacher Profiling Tool Kyushu University Pure
http://www.me.inf.kyushu-u.ac.jp/en/member.html
Academic Degree
Dr.Eng
Country of degree conferring institution (Overseas)
No
Field of Specialization
Learning Theory, Information Theory, Machine Learning
Total Priod of education and research career in the foreign country
01years01months
Research
Research Interests
  • Information-Based Induction Sciences and its Application
    keyword : Learning Theory, Information Theory, Stochastic Complexity, Information Geometry, Machine Learning, Super Resulution, Cyber Security, MRI
    2006.04.
Academic Activities
Books
1. Jun'ichi Takeuchi, ``An introduction to 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. Chansu HAN, Jumpei SHIMAMURA, Takeshi TAKAHASHI, Daisuke INOUE, Jun'ichi TAKEUCHI, Koji NAKAO, Real-time Detection of Global Cyberthreat Based on Darknet by Estimating Anomalous Synchronization Using Graphical Lasso, IEICE Transactions, Vol.E103-D, No.10, 2020.10.
2. Masanori Kawakita, Jun'ichi Takeuchi, Minimum Description Length Principle in Supervised Learning With Application to Lasso, IEEE Transactions on Information Theory, 10.1109/TIT.2020.2998577, 66, 7, 4245-4269 , 2020.07, [URL].
3. Yoshinari Takeishi, Jun'ichi Takeuchi, An Improved Analysis of Least Squares Superposition Codes with Bernoulli Dictionary, Japanese Journal of Statistics and Data Science, Vol. 2, Issue 2, 2019.12.
4. Masanori Kawakita, Jun'ichi Takeuchi, A Note on Model Selection for Small Sample Regression, Machine Learning, 106, 11, 1839-1862, 2017.11.
5. 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, 2737-2750, 2014.05.
6. Masanori Kawakita, Jun'ichi Takeuchi, Safe Semi-supervised Learning Based on Weighted Likelihood, Neural Networks, 53, 146-164, 2014.05.
7. Jun'ichi Takeuchi, Tsutomu Kawabata, Andrew R. Barron, Properties of Jeffreys mixture of Markov Sources, IEEE transactions on Information Theory, 59, 1, 438-457, 2013.01.
8. 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.
9. J. Takeuchi & S. Amari, α-Parallel Prior and Its Properties, IEEE transactions on Information Theory, Vol. 51, No. 3, pp. 1011-1023, 2005.03.
10. 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.
11. J. Takeuchi, N. Abe, & S. Amari, The Lob-Pass problem, Journal of Computer and System Sciences, 2000.03.
12. 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. Kohei Miyamoto, Jun'ichi Takeuchi, On MDL Estimation for Simple Contaminated Gaussian Location Families, The International Symposium on Information Theory and Its Applications 2020, 2020.10.
2. Shizen Kitazaki, Masanori Kawakita, Yutaka Jitsumatsu, Shigehide Kuhara, Akio Hiwatashi, Jun'ichi Takeuchi, Magnetic Resonance Angiography Image Restoration by Super Resolution Based on Deep Learning, The 2019 World Congress of the European Society for Magnetic Resonance in Medicine and Biology, 2019.10.
3. Chansu Han, Jumpei Shimamura, Takeshi Takahashi, Daisuke Inoue, Masanori Kawakita, Jun'ichi Takeuchi, Koji Nakao, Real-Time Detection of Malware Activities by Analyzing Darknet Traffic Using Graphical Lasso, The 18th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, 2019.08.
4. Kazushi Mimura, Jun'ichi Takeuchi, Dynamics of Damped Approximate Message Passing Algorithms, 2019 IEEE Information Theory Workshop, 2019.08.
5. Kohei Miyamoto, Andrew R. Barron, Jun'ichi Takeuchi, Improved MDL Estimators Using Local Exponential Family Bundles Applied to Mixture Families, 2019 IEEE International Sympojium on Information Theory, 2019.07, [URL].
6. Jun'ichi Takeuchi, Hiroshi Nagaoka, Information Geometry of The Family of Markov Kernels Defined by A Context Tree, 2017 IEEE Information Theory Workshop, 2017.10.
7. Shoma Tanaka, Yuki Kawamura, Masanori Kawakita, Jun'ichi Takeuchi, MDL criterion for NMF with Application to Botnet Detection, the 2016 Data Mining and Cybersecurity Workshop, associated with the 23rd International Conference on Neural Information Processing,, 2016.10.
8. Chan-su Han, Kento Kono, Masanori Kawakita, Jun'ichi Takeuchi, Botnet Detection Using Graphical Lasso with Graph Density, the 2016 Data Mining and Cybersecurity Workshop, associated with the 23rd International Conference on Neural Information Processing,, 2016.10.
9. 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. 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.
11. Jun'ichi Takeuchi, Andrew R. Barron, Stochastic complexity for tree models, 2014 IEEE Information Theory Workshop, 2014.11.
12. Jun'ichi Takeuchi, Andrew R. Barron, Asymptotically minimax regret for models with hidden variables, 2014 IEEE International Symposium on Information Theory, 2014.07.
13. Jun'ichi Takeuchi, Andrew R. Barron, Asymptotically Minimax Regret by Bayes Mixtures for Non-exponential Families, 2013 IEEE Information Theory Workshop, 2013.09.
14. 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.
15. 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.
16. Jun'ichi Takeuchi, Yoshinari Takeishi, Sparse Superposition Codes with Discrete Dictionary, The 5th Workshop on Information Theoretic Methods in Science and Engineering, 2012.08.
17. 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.