Keiichi Kisamori, Keisuke Yamazaki. Intractable Likelihood Regression for Covariate Shift by Kernel Mean Embedding. CoRR. 2018. abs/1809.08159
Takafumi Kajihara, Motonobu Kanagawa, Keisuke Yamazaki, Kenji Fukumizu. Kernel Recursive ABC: Point Estimation with Intractable Likelihood. Proceedings of the 35th International Conference on Machine Learning, ICML 2018, Stockholmsmässan, Stockholm, Sweden, July 10-15, 2018. 2018. 2405-2414
Keisuke Yamazaki, Yoichi Motomura. Hidden Node Detection between Two Observable Nodes Based on Bayesian Clustering. Proceedings of the 3rd Workshop on Advanced Methodologies for Bayesian Networks, AMBN 2017, Kyoto, Japan, September 20-22, 2017. 2017. 165-175
NAKAMURA Fumito, YAMAZAKI Keisuke. Modeling and Grouping Optimal Speeds Based on Traffic-Flow Video. IEICE technical report. Image engineering. 2015. 114. 460. 155-160
YAMAZAKI Keisuke. An Accuracy Analysis of Latent Variables Estimation with the Maximum Likelihood Estimator. 2011. 111. 275. 87-91
YAMAZAKI Keisuke. Bayesian State Estimation and its Accuracy Analysis on Hidden Markov Models. IEICE technical report. 2011. 111. 87. 37-42
YAMAZAKI Keisuke. A Theoretical Analysis of KL-type Generalization Error on Hidden Variable Distribution. IEICE technical report. 2011. 110. 461. 223-228
MIKI Takushi, YAMAZAKI Keisuke, WATANABE Sumio. Comparison between the Parameter and the Hidden Variable Space for Calculation of the Marginal Likelihood. IEICE technical report. 2011. 110. 461. 289-294
Newton Diagram and Stochastic Complexity in Mixture of Binomial Distributions
Lecture Notes in Artificial Intelligence 2004
Newton Diagram and Stochastic Complexity in Mixture of Binomial Distributions
Lecture Notes in Artificial Intelligence 2004
Lectures and oral presentations (12)：
An Analysis of Generalization Error in Relevant Subtask Learning
(International Conference on Neural Information Processing of the Asia-Pacific Neural Network Assembly 2008)
An Analysis of Generalization Error in Relevant Subtask Learning
(International Conference on Neural Information Processing of the Asia-Pacific Neural Network Assembly 2008)
Asymptotic Bayesian Generalization Error When Training and Test Distributions Are Different
(Proc. of ICML 2007)
Experimental Bayesian Generalization Error of Non-Regular Models under Covariate Shift
(International Conference on Neural Information Processing 2007)
Asymptotic Bayesian Generalization Error When Training and Test Distributions Are Different
(Proc. of ICML 2007)
- 2004 Tokyo Institute of Technology Graduate School, Division of Integrated Science and Engineering
- 2004 Tokyo Institute of Technology Interdisciplinary Science and Engineering Intelligent Systems Science
- 2001 Tokyo Institute of Technology School of Engineering Department of Computer Science
Professional career (1)：
Doctor of Engineering (Tokyo Institute of Technology)
Work history (3)：
2004 - -:
2004 - -:東京工業大学 精密工学研究所 助手
Tokyo Institute of Technology Interdisciplinary Graduate School of Science and Engineering, Department of Computational Intelligence and Systems Science Assistant Professor
Awards (2)：
2004 - Japan Neurarl Network Society Young Researcher Award
2004 - 日本神経回路学会 奨励賞
Association Membership(s) (5)：
Information and Communication Engineers
, The Institute of Electronics
, Japan Neural Networks Society
, 電子情報通信学会
, 日本神経回路学会
