# Takeru Matsuda, Ph.D.

Unit Leader, Statistical Mathematics Unit

takeru.matsuda [at] riken.jp

## Research Overview

With recent advances in experimental technologies, large-scale and diverse brain data are now available. To extract more information from such brain data, we develop tailored statistical methods by translating the characteristics of data into the form of statistical models. We incorporate techniques from applied mathematics, such as numerical analysis and optimization, to develop efficient methods that are applicable to large-scale data. We also investigate the fundamental theory of statistics.

### Main Research Field

Informatics

### Related Research Fields

Interdisciplinary science and engineering

Mathematical and physical sciences

Statistical science

Mathematical informatics

### Keywords

- Statistics
- Applied mathematics
- Data analysis
- Machine learning

## Selected Publications

- Uehara, M., Matsuda, T. and Kim, J. K.

Imputation estimators for unnormalized models with missing data

23rd International Conference on Artificial Intelligence and Statistics (AISTATS 2020). - Xu, W. and Matsuda, T.

A Stein goodness-of-fit test for directional distributions

23rd International Conference on Artificial Intelligence and Statistics (AISTATS 2020). - Matsuda, T. and Hyvarinen, A.

Estimation of non-normalized mixture models

22nd International Conference on Artificial Intelligence and Statistics (AISTATS 2019). - Matsuda, T. and Strawderman, W. E.

Improved loss estimation for a normal mean matrix

Journal of Multivariate Analysis 169, 300--311, 2019. - Matsuda, T. and Komaki, F.

Empirical Bayes matrix completion

Computational Statistics & Data Analysis 137, 195--210, 2019. - Maruyama, Y., Matsuda, T. and Ohnishi, T.

Harmonic Bayesian prediction under alpha-divergence

IEEE Transactions on Information Theory 65, 5352-5366, 2019. - Matsuda, T. and Komaki, F.

Multivariate time series decomposition into oscillation components

Neural Computation 29, 2055--2075, 2017. - Matsuda, T. and Komaki, F.

Time series decomposition into oscillation components and phase estimation

Neural Computation 29, 332--367, 2017. - Matsuda, T., Kitajo, K., Yamaguchi, Y. and Komaki, F.

A point process modeling approach for investigating the effect of online brain activity on perceptual switching

NeuroImage 152, 50--59, 2017. - Matsuda, T. and Komaki, F.

Singular value shrinkage priors for Bayesian prediction

Biometrika 102, 843--854, 2015.