# Keisuke Yamazaki

According to our database

Collaborative distances:

^{1}, Keisuke Yamazaki authored at least 38 papers between 2003 and 2020.Collaborative distances:

## Timeline

#### Legend:

Book In proceedings Article PhD thesis Other## Links

#### On csauthors.net:

## Bibliography

2020

Simulator Calibration under Covariate Shift with Kernels.

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Hidden Node Detection between Observable Nodes Based on Bayesian Clustering.

Entropy, 2019

Model Bridging: To Interpretable Simulation Model From Neural Network.

CoRR, 2019

2018

Bayesian estimation of multidimensional latent variables and its asymptotic accuracy.

Neural Networks, 2018

Intractable Likelihood Regression for Covariate Shift by Kernel Mean Embedding.

CoRR, 2018

Kernel Recursive ABC: Point Estimation with Intractable Likelihood.

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

Effects of additional data on Bayesian clustering.

Neural Networks, 2017

A Risk Information Provision System on Bicycle Parking Lots.

Proceedings of the IEEE International Congress on Internet of Things, 2017

Hidden Node Detection between Two Observable Nodes Based on Bayesian Clustering.

Proceedings of the 3rd Workshop on Advanced Methodologies for Bayesian Networks, 2017

2016

Asymptotic accuracy of Bayes estimation for latent variables with redundancy.

Mach. Learn., 2016

2015

Asymptotic accuracy of Bayesian estimation for a single latent variable.

Neural Networks, 2015

Accuracy of latent-variable estimation in Bayesian semi-supervised learning.

Neural Networks, 2015

On the Optimal Hyperparameter Behavior in Bayesian Clustering.

JACIII, 2015

Accuracy analysis of semi-supervised classification when the class balance changes.

Neurocomputing, 2015

2014

Asymptotic accuracy of distribution-based estimation of latent variables.

J. Mach. Learn. Res., 2014

On Bayesian Clustering with a Structured Gaussian Mixture.

JACIII, 2014

Asymptotic Marginal Likelihood on Linear Dynamical Systems.

IEICE Trans. Inf. Syst., 2014

The optimal hyperparameter for Bayesian clustering and its application to the evaluation of clustering results.

Proceedings of the 2014 Joint 7th International Conference on Soft Computing and Intelligent Systems (SCIS) and 15th International Symposium on Advanced Intelligent Systems (ISIS), 2014

Two statistical methods for grouping vehicles in traffic flow based on probabilistic cellular automata.

Proceedings of the 2014 Joint 7th International Conference on Soft Computing and Intelligent Systems (SCIS) and 15th International Symposium on Advanced Intelligent Systems (ISIS), 2014

2013

Comparing two Bayes methods based on the free energy functions in Bernoulli mixtures.

Neural Networks, 2013

A Geometric Evaluation of Self-Organizing Map and Application to City Data Analysis.

Proceedings of the Multi-disciplinary Trends in Artificial Intelligence, 2013

2012

On equivalent parameter learning in simplified feature space based on Bayesian asymptotic analysis.

Neural Networks, 2012

MCMC sampling on latent-variable space of mixture of probabilistic PCA.

Proceedings of the 6th International Conference on Soft Computing and Intelligent Systems (SCIS), 2012

Accuracy of latent variable estimation with the maximum likelihood estimator for partially observed hidden data.

Proceedings of the International Symposium on Information Theory and its Applications, 2012

Parameter estimation accuracy and active learning in the zero-range process.

Proceedings of the 12th International Conference on Intelligent Systems Design and Applications, 2012

2011

An asymptotic analysis of Bayesian state estimation in hidden Markov models.

Proceedings of the 2011 IEEE International Workshop on Machine Learning for Signal Processing, 2011

2010

Asymptotic analysis of Bayesian generalization error with Newton diagram.

Neural Networks, 2010

2009

A Study on Bayesian Learning of One-Dimensional Linear Dynamical Systems.

Proceedings of the Neural Information Processing, 16th International Conference, 2009

2008

An Analysis of Generalization Error in Relevant Subtask Learning.

Proceedings of the Advances in Neuro-Information Processing, 15th International Conference, 2008

2007

Experimental Bayesian Generalization Error of Non-regular Models under Covariate Shift.

Proceedings of the Neural Information Processing, 14th International Conference, 2007

Asymptotic Bayesian generalization error when training and test distributions are different.

Proceedings of the Machine Learning, 2007

2006

A Model Selection Method Based on Bound of Learning Coefficient.

Proceedings of the Artificial Neural Networks, 2006

2005

Singularities in complete bipartite graph-type Boltzmann machines and upper bounds of stochastic complexities.

IEEE Trans. Neural Networks, 2005

Algebraic geometry and stochastic complexity of hidden Markov models.

Neurocomputing, 2005

2004

Newton Diagram and Stochastic Complexity in Mixture of Binomial Distributions.

Proceedings of the Algorithmic Learning Theory, 15th International Conference, 2004

2003

Singularities in mixture models and upper bounds of stochastic complexity.

Neural Networks, 2003

Stochastic Complexity of Bayesian Networks.

Proceedings of the UAI '03, 2003

Stochastic complexities of hidden Markov models.

Proceedings of the NNSP 2003, 2003