| Singularities in mixture models and upper bounds of stochastic complexity K Yamazaki, S Watanabe Neural networks 16 (7), 1029-1038, 2003 | 143 | 2003 |
| Algebraic geometry and stochastic complexity of hidden Markov models K Yamazaki, S Watanabe Neurocomputing 69 (1-3), 62-84, 2005 | 43 | 2005 |
| Stochastic complexity of Bayesian networks K Yamazaki, S Watanbe arXiv preprint arXiv:1212.2511, 2012 | 42 | 2012 |
| Asymptotic bayesian generalization error when training and test distributions are different K Yamazaki, M Kawanabe, S Watanabe, M Sugiyama, KR Müller Proceedings of the 24th international conference on Machine learning, 1079-1086, 2007 | 37 | 2007 |
| Singularities in complete bipartite graph-type boltzmann machines and upper bounds of stochastic complexities K Yamazaki, S Watanabe IEEE transactions on neural networks 16 (2), 312-324, 2005 | 37 | 2005 |
| Kullback information of normal mixture is not an analytic function 青柳美輝 Technical report of IEICE, NC2004, 41-46, 2004 | 37 | 2004 |
| Stochastic complexities of hidden Markov models K Yamazaki, S Watanabe 2003 IEEE XIII Workshop on Neural Networks for Signal Processing (IEEE Cat …, 2003 | 23 | 2003 |
| Newton diagram and stochastic complexity in mixture of binomial distributions K Yamazaki, S Watanabe Algorithmic Learning Theory: 15th International Conference, ALT 2004, Padova …, 2004 | 22 | 2004 |
| Asymptotic analysis of Bayesian generalization error with Newton diagram K Yamazaki, M Aoyagi, S Watanabe Neural Networks 23 (1), 35-43, 2010 | 21 | 2010 |
| Kernel recursive ABC: Point estimation with intractable likelihood T Kajihara, M Kanagawa, K Yamazaki, K Fukumizu International Conference on Machine Learning, 2400-2409, 2018 | 17 | 2018 |
| Comparing two Bayes methods based on the free energy functions in Bernoulli mixtures K Yamazaki, D Kaji Neural networks 44, 36-43, 2013 | 16 | 2013 |
| Asymptotic accuracy of Bayes estimation for latent variables with redundancy K Yamazaki Machine Learning 102 (1), 1-28, 2016 | 14 | 2016 |
| Asymptotic accuracy of distribution-based estimation of latent variables. K Yamazaki J. Mach. Learn. Res. 15 (1), 3541-3562, 2014 | 14 | 2014 |
| A new method of model selection based on learning coefficient K Yamazaki, K Nagata, S Watanabe IEICE Proceedings Series 40 (3-1-5-2), 2005 | 13 | 2005 |
| A probabilistic algorithm to calculate the learning curves of hierarchical learning machines with singularities K YAMAZAKI Trans. on IEICE, D-II, 2002 | 13 | 2002 |
| Simulator calibration under covariate shift with kernels K Kisamori, M Kanagawa, K Yamazaki International Conference on Artificial Intelligence and Statistics, 1244-1253, 2020 | 11* | 2020 |
| Development of a new type of open rack LNG vaporizer K Yamazaki, T Shimokawatoko, Y Yamasaki, M Takata, K Shikai, ... International Conference on LNG, 12th, B, 2-10, 1998 | 11 | 1998 |
| Amorphous state formation and structural changes in a alumina by repeated rubbing H Furuichi, K Matsuura, K Yamazaki, S Watanabe Wear 189 (1-2), 86-90, 1995 | 11 | 1995 |
| Accuracy analysis of semi-supervised classification when the class balance changes K Yamazaki Neurocomputing 160, 132-140, 2015 | 9 | 2015 |
| Development of an integrated AI platform and an ecosystem for daily life, business and social problems K Takaoka, K Yamazaki, E Sakurai, K Yamashita, Y Motomura Advances in Artificial Intelligence, Software and Systems Engineering: Joint …, 2019 | 7 | 2019 |
