Michiko Okudo
Michiko Okudo
Associate Professor
Department of Mathematics and Informatics
Faculty of Science, Chiba University, Japan
E-mail: okudo [at] math.s.chiba-u.ac.jp
2025.9-: Associate Professor, Chiba University
2020.4-2025.8: Assistant Professor, University of Tokyo
2018.4-2020.3: JSPS Research Fellow (DC2)
2020.3: Ph.D of Information Science and Technology from Graduate School of Information Science and Technology, University of Tokyo
2017.3: Master of Information Science and Technology from Graduate School of Information Science and Technology, University of Tokyo
2015.3: Bachelor of Engineering from Faculty of Engineering, University of Tokyo
Shrinkage priors for circulant correlation structure models. [Journal Website]
M. Okudo and T. Sei.
Information Geometry, accepted.
Matching prior pairs connecting Maximum A Posteriori estimation and posterior expectation. [Journal Website]
M. Okudo and K. Yano.
Bayesian Analysis, accepted.
Predictive densities for multivariate normal models based on extended models and shrinkage Bayes methods. [Journal Website]
M. Okudo and F. Komaki.
Electronic Journal of Statistics, vol. 18, 3310--3326, 2024.
Shrinkage priors for single-spiked covariance models. [Journal Website]
M. Okudo and F. Komaki.
Statistics & Probability Letters, vol. 176, 109127, 2021.
Bayes extended estimators for curved exponential families. [Journal Website]
M. Okudo and F. Komaki.
IEEE Transactions on Information Theory, vol. 67, pp. 1088--1098, 2021.
Hamiltonian Monte Carlo with explicit, reversible, and volume-preserving adaptive step size control. [Journal Website]
M. Okudo and H. Suzuki.
JSIAM Letters, vol. 9, pp. 33--36, 2017.
Shrinkage priors for models with circulant correlation structure
M. Okudo and T. Sei, Further Developments of Information Geometry (FDIG2025), Tokyo, 2025.3.
Bayes extended estimators with shrinkage priors for multivariate normal models
M. Okudo and F. Komaki, EcoSta 2022, Kyoto, 2022.6.
Asymptotic properties of Bayes estimators based on shrinkage priors for curved exponential families.
M. Okudo, EAC-ISBA 2019, Kobe, 2019.7.
Scale-invariant estimations for the factor analysis model based on its geometric structure.
M. Okudo and F. Komaki, CMStatistics 2018, Italy, 2018.12.
Priors for the factor analysis model based on its geometric structure.
M. Okudo, 5th IMS Asia Pacific Rim Meeting (ims-APRM 2018), Singapore, 2018.6.
Ogawa Award, Japan Statistical Society (2025)
Presentation Award, Japanese Joint Statistical Meeting (2019.9)
Paper Award from the Japan Society for Industrial and Applied Mathematics (JSIAM) (2018.9)