Takeru Matsuda

Takeru Matsuda, Ph.D.

Unit Leader, Statistical Mathematics Collaboration 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.

Selected Publications

  1. Matsuda, T. and Strawderman, W. E.
    "Estimation under matrix quadratic loss and matrix superharmonicity"
    Biometrika, to appear.
  2. Matsuda, T., Homae. F., Watanabe, H., Taga, G. and Komaki, F.
    "Oscillator decomposition of infant fNIRS data"
    PLOS Computational Biology, 18(3), e1009985, 2022.
  3. Amari, S. and Matsuda, T.
    "Wasserstein statistics in one-dimensional location-scale models"
    Annals of the Institute of Statistical Mathematics, 74, 33–47, 2022.
  4. Matsuda, T., Uehara, M. and Hyvarinen, A.
    "Information criteria for non-normalized models"
    Journal of Machine Learning Research, 22(158):1−33, 2021.
  5. Matsuda. T. and Miyatake, Y.
    "Estimation of ordinary differential equation models with discretization error quantification"
    SIAM/ASA Journal on Uncertainty Quantification, 9, 302–331, 2021.
  6. Matsuda, T.
    "Statistical analysis of kimariji in competitive karuta (in Japanese)"
    Japanese Journal of Applied Statistics, 49, 1--11, 2020.
  7. Matsuda, T. and Hyvarinen, A.
    "Estimation of non-normalized mixture models"
    22nd International Conference on Artificial Intelligence and Statistics (AISTATS 2019).
  8. Y. Maruyama, T. Matsuda and T. Onishi.
    "Harmonic Bayesian prediction under alpha-divergence"
    IEEE Transactions on Information Theory, 65, 5352--5366, 2019.
  9. Matsuda, T. and Komaki, F.
    "Time series decomposition into oscillation components and phase estimation"
    Neural Computation 29, 332--367, 2017.
  10. Matsuda, T. and Komaki, F.
    "Singular value shrinkage priors for Bayesian prediction"
    Biometrika 102, 843--854, 2015.

News & Media