Keisuke Yamazaki

Publication Activity (10 Years)

Years Active: 2003-2023
Publications (10 Years): 21

Top Topics

Cellular Automata

Covariate Shift

Bayesian Estimation

Latent Variables

Top Venues

Neural Networks

J. Adv. Comput. Intell. Intell. Informatics

Publications

Lincon S. Souza, Bojan Batalo, Keisuke Yamazaki
A Geometric Surrogate for Simulation Calibration. ICASSP (2023)
Yoriyuki Yamagata, Shunki Takami, Keisuke Yamazaki, Tomoki Nakaya, Masaki Onishi
Individual-based epidemiological model of COVID19 using location data. Big Data (2022)
Tomoya Kitamura, Atsumi Saito, Keisuke Yamazaki, Yuki Saito, Hiroshi Asai, Kouhei Ohnishi
Validation of a Property Estimation Method Based on Sequential and Posteriori Estimation. IECON (2022)
Keisuke Yamazaki, Satoshi Tamura, Yuuto Gotoh, Masaki Nose
Visual-only Voice Activity Detection using Human Motion in Conference Video. ICPRAM (2022)
Daichi Yanagisawa, Keisuke Yamazaki
Detecting aggressive agents in egress process by using conflict data in cellular automaton model. J. Intell. Transp. Syst. 25 (6) (2021)
Rina Komatsu, Keisuke Yamazaki
Conditional Drive Environment Translation using StarGAN with CBIN. AICCC (2021)
Keiichi Kisamori, Motonobu Kanagawa, Keisuke Yamazaki
Simulator Calibration under Covariate Shift with Kernels. AISTATS (2020)
Keiichi Kisamori, Keisuke Yamazaki, Yuto Komori, Hiroshi Tokieda
Model Bridging: Connection Between Simulation Model and Neural Network. ECML/PKDD (5) (2020)
Keiichi Kisamori, Keisuke Yamazaki
Model Bridging: To Interpretable Simulation Model From Neural Network. CoRR (2019)
Keisuke Yamazaki, Yoichi Motomura
Hidden Node Detection between Observable Nodes Based on Bayesian Clustering. Entropy 21 (1) (2019)
Takafumi Kajihara, Motonobu Kanagawa, Keisuke Yamazaki, Kenji Fukumizu
Kernel Recursive ABC: Point Estimation with Intractable Likelihood. ICML (2018)
Keiichi Kisamori, Keisuke Yamazaki
Intractable Likelihood Regression for Covariate Shift by Kernel Mean Embedding. CoRR (2018)
Keisuke Yamazaki
Bayesian estimation of multidimensional latent variables and its asymptotic accuracy. Neural Networks 105 (2018)
Keisuke Yamazaki, Yoichi Motomura
Hidden Node Detection between Two Observable Nodes Based on Bayesian Clustering. AMBN (2017)
Keisuke Yamazaki
Effects of additional data on Bayesian clustering. Neural Networks 94 (2017)
Keisuke Yamazaki, Tsuyoshi Nakajima
A Risk Information Provision System on Bicycle Parking Lots. ICIOT (2017)
Keisuke Yamazaki
Asymptotic accuracy of Bayes estimation for latent variables with redundancy. Mach. Learn. 102 (1) (2016)
Keisuke Yamazaki
Accuracy analysis of semi-supervised classification when the class balance changes. Neurocomputing 160 (2015)
Keisuke Yamazaki
On the Optimal Hyperparameter Behavior in Bayesian Clustering. J. Adv. Comput. Intell. Intell. Informatics 19 (6) (2015)
Keisuke Yamazaki
Asymptotic accuracy of Bayesian estimation for a single latent variable. Neural Networks 69 (2015)
Keisuke Yamazaki
Accuracy of latent-variable estimation in Bayesian semi-supervised learning. Neural Networks 69 (2015)
Keisuke Yamazaki
On Bayesian Clustering with a Structured Gaussian Mixture. J. Adv. Comput. Intell. Intell. Informatics 18 (6) (2014)
Fumito Nakamura, Keisuke Yamazaki
Two statistical methods for grouping vehicles in traffic flow based on probabilistic cellular automata. SCIS&ISIS (2014)
Keisuke Yamazaki
Asymptotic accuracy of distribution-based estimation of latent variables. J. Mach. Learn. Res. 15 (1) (2014)
Takuto Naito, Keisuke Yamazaki
Asymptotic Marginal Likelihood on Linear Dynamical Systems. IEICE Trans. Inf. Syst. (4) (2014)
Keisuke Yamazaki
The optimal hyperparameter for Bayesian clustering and its application to the evaluation of clustering results. SCIS&ISIS (2014)
Keisuke Yamazaki
Asymptotic Accuracy of Bayesian Estimation for a Single Latent Variable. CoRR (2014)
Shigehiro Ohara, Keisuke Yamazaki, Sumio Watanabe
A Geometric Evaluation of Self-Organizing Map and Application to City Data Analysis. MIWAI (2013)
Keisuke Yamazaki, Daisuke Kaji
Comparing two Bayes methods based on the free energy functions in Bernoulli mixtures. Neural Networks 44 (2013)
Keisuke Yamazaki
Asymptotic Accuracy of Distribution-Based Estimation for Latent Variables CoRR (2012)
Keisuke Yamazaki
Accuracy of latent variable estimation with the maximum likelihood estimator for partially observed hidden data. ISITA (2012)
Koichi Kobayashi, Keisuke Yamazaki
Parameter estimation accuracy and active learning in the zero-range process. ISDA (2012)
Keisuke Yamazaki, Sumio Watanabe
Stochastic complexity of Bayesian networks CoRR (2012)
Keisuke Yamazaki
MCMC sampling on latent-variable space of mixture of probabilistic PCA. SCIS&ISIS (2012)
Keisuke Yamazaki
On equivalent parameter learning in simplified feature space based on Bayesian asymptotic analysis. Neural Networks 31 (2012)
Keisuke Yamazaki
An asymptotic analysis of Bayesian state estimation in hidden Markov models. MLSP (2011)
Keisuke Yamazaki, Miki Aoyagi, Sumio Watanabe
Asymptotic analysis of Bayesian generalization error with Newton diagram. Neural Networks 23 (1) (2010)
Takuto Naito, Keisuke Yamazaki
A Study on Bayesian Learning of One-Dimensional Linear Dynamical Systems. ICONIP (1) (2009)
Keisuke Yamazaki, Samuel Kaski
An Analysis of Generalization Error in Relevant Subtask Learning. ICONIP (1) (2008)
Keisuke Yamazaki, Sumio Watanabe
Experimental Bayesian Generalization Error of Non-regular Models under Covariate Shift. ICONIP (1) (2007)
Keisuke Yamazaki, Motoaki Kawanabe, Sumio Watanabe, Masashi Sugiyama, Klaus-Robert Müller
Asymptotic Bayesian generalization error when training and test distributions are different. ICML (2007)
Keisuke Yamazaki, Kenji Nagata, Sumio Watanabe, Klaus-Robert Müller
A Model Selection Method Based on Bound of Learning Coefficient. ICANN (2) (2006)
Keisuke Yamazaki, Sumio Watanabe
Algebraic geometry and stochastic complexity of hidden Markov models. Neurocomputing 69 (1-3) (2005)
Keisuke Yamazaki, Sumio Watanabe
Singularities in complete bipartite graph-type Boltzmann machines and upper bounds of stochastic complexities. IEEE Trans. Neural Networks 16 (2) (2005)
Keisuke Yamazaki, Sumio Watanabe
Newton Diagram and Stochastic Complexity in Mixture of Binomial Distributions. ALT (2004)
Keisuke Yamazaki, Sumio Watanabe
Stochastic Complexity of Bayesian Networks. UAI (2003)
Keisuke Yamazaki, Sumio Watanabe
Stochastic complexities of hidden Markov models. NNSP (2003)
Keisuke Yamazaki, Sumio Watanabe
Singularities in mixture models and upper bounds of stochastic complexity. Neural Networks 16 (7) (2003)