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
山崎 啓介. An Accuracy Analysis of Latent Variables Estimation with the Maximum Likelihood Estimator (情報論的学習理論と機械学習). 電子情報通信学会技術研究報告 : 信学技報. 2011. 111. 275. 87-91
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
講演・口頭発表等 (12件)：
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)
