Yamazaki Keisuke

J-GLOBAL         Last updated: Nov 1, 2018 at 11:40
 
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Name
Yamazaki Keisuke
Degree
Doctor of Engineering(Tokyo Institute of Technology)

Research Interests

 
 

Research Areas

 
 

Academic & Professional Experience

 
 
   
 
Assistant Professor, Tokyo Institute of Technology Interdisciplinary Graduate School of Science and Engineering, Department of Computational Intelligence and Systems Science
 
2004
   
 
-:
 

Education

 
 
 - 
2004
Graduate School, Division of Integrated Science and Engineering, Tokyo Institute of Technology
 

Awards & Honors

 
2004
Japan Neurarl Network Society Young Researcher Award
 

Published Papers

 
Keiichi Kisamori,Keisuke Yamazaki
CoRR   abs/1809.08159    2018   [Refereed]
Takafumi Kajihara,Motonobu Kanagawa,Keisuke Yamazaki,Kenji Fukumizu
Proceedings of the 35th International Conference on Machine Learning, ICML 2018, Stockholmsmässan, Stockholm, Sweden, July 10-15, 2018   2405-2414   2018   [Refereed]
Keisuke Yamazaki
Neural Networks   105 14-25   2018   [Refereed]
Keisuke Yamazaki,Yoichi Motomura
Proceedings of the 3rd Workshop on Advanced Methodologies for Bayesian Networks, AMBN 2017, Kyoto, Japan, September 20-22, 2017   165-175   2017   [Refereed]
Keisuke Yamazaki
Neural Networks   94 86-95   2017   [Refereed]

Misc

 
Keisuke Yamazaki, Miki Aoyagi, Sumio Watanabe
Neural Networks   23(1) 35-43   2010
Stochastic Complexity and Newton Diagram
Keisuke Yamazaki Miki Aoyagi Sumio Watanabe
Proceedings of International Symposium on Information Theory and its Applications (ISITA2004)   105-110   2004
Keisuke Yamazaki Sumio Watanabe
Proceedings of Neural Networks for Signal Processing XIII (NNSP'03)   179-188   2003
Stochastic Complexity of Bayesian Networks
Keisuke Yamazaki Sumio Watanabe
Proceedings of Uncertainty in Artificial Intelligence (UAI'03)   592-599   2003
Keisuke Yamazaki Sumio Watanabe
International Journal of Neural Networks   16 1029-1038   2003

Books etc

 
Newton Diagram and Stochastic Complexity in Mixture of Binomial Distributions
Lecture Notes in Artificial Intelligence   2004   ISBN:03029743

Conference Activities & Talks

 
An Analysis of Generalization Error in Relevant Subtask Learning
International Conference on Neural Information Processing of the Asia-Pacific Neural Network Assembly   2008   
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   
A Model Selection Method Based on Bound of Learning Coefficient
Proc. of International Conference on Artificial Neural Networks   2006   
A New Method of Model Selection Based on Learning Coefficient
Proc. of International Symposium on Nonlinear Theory and its Applications   2005