Double shrinkage priors for a normal mean matrix. [arXiv]
T. Matsuda, F. Komaki and W. E. Strawderman.
Minimaxity under half-Cauchy type priors. [arXiv]
Y. Maruyama and T. Matsuda.
Information geometry of Wasserstein statistics on shapes and affine deformations. [arXiv]
S. Amari and T. Matsuda.
Asymptotic analysis of parameter estimation for the Ewens--Pitman partition. [arXiv]
T. Koriyama, T. Matsuda and F. Komaki.
Generalized nearly isotonic regression. [arXiv]
T. Matsuda and Y. Miyatake.
Analysis of noise contrastive estimation from the perspective of asymptotic variance. [arXiv]
M. Uehara, T. Matsuda and F. Komaki.
査読付き論文誌・国際会議
Adapting to general quadratic loss via singular value shrinkage. [Journal Website]
T. Matsuda. IEEE Transactions on Information Theory, accepted.
Modelling the discretization error of initial value problems using the Wishart distribution. [Journal Website]
N. Marumo, T. Matsuda and Y. Miyatake. Applied Mathematics Letters, 147, 108833, 2024.
Matrix quadratic risk of orthogonally invariant estimators for a normal mean matrix. [Journal Website]
T. Matsuda. Japanese Journal of Statistics and Data Science, accepted.
Inadmissibility of the corrected Akaike information criterion. [arXiv]
T. Matsuda. Bernoulli, accepted.
Advanced paternal age diversifies individual trajectories of vocalization patterns in neonatal mice. [Journal Website]
L. Mai, H. Inada, R. Kimura, K. Kanno, T. Matsuda, R. Tachibana, V. Tucci, F. Komaki, N. Hiroi and N. Osumi. iScience, 25, 104834, 2022.
Information geometry of operator scaling. [Journal Website]
T. Matsuda and T. Soma. Linear Algebra and Its Applications, 649, 240--267, 2022.
Estimation under matrix quadratic loss and matrix superharmonicity. [Journal Website] [press release]
T. Matsuda and W. E. Strawderman. Biometrika, 109, 503--519, 2022.
Oscillator decomposition of infant fNIRS data. [Journal Website] [MATLAB code]
T. Matsuda, F. Homae, H. Watanabe, G. Taga and F. Komaki. PLOS Computational Biology, 18(3), e1009985, 2022.
Wasserstein statistics in one-dimensional location-scale models. [Journal Website] [arXiv]
S. Amari and T. Matsuda. Annals of the Institute of Statistical Mathematics, 74, 33–47, 2022.
Information criteria for non-normalized models. [Journal Website]
T. Matsuda, M. Uehara and A. Hyvarinen. Journal of Machine Learning Research, 22(158):1−33, 2021.
Interpretable Stein Goodness-of-fit Tests on Riemannian Manifolds. [Proceedings Website]
W. Xu and T. Matsuda. Proceedings of the 38th International Conference on Machine Learning (ICML 2021)., 2021.
Estimation of ordinary differential equation models with discretization error quantification. [Journal Website] [arXiv]
T. Matsuda and Y. Miyatake. SIAM/ASA Journal on Uncertainty Quantification, 9, 302–331, 2021.
Generalization of partitioned Runge--Kutta methods for adjoint systems. [Journal Website]
T. Matsuda and Y. Miyatake. Journal of Computational and Applied Mathematics, 388, 113308, 2021.
Adjoint-based exact Hessian computation. [Journal Website]
S. Ito, T. Matsuda and Y. Miyatake. BIT Numerical Mathematics, 61, 503–522, 2021.
Predictive density estimation under the Wasserstein loss. [Journal Website]
T. Matsuda and W. E. Strawderman. Journal of Statistical Planning and Inference, 210, 53--63, 2021.
Imputation estimators for unnormalized models with missing data. [Proceedings Website]
M. Uehara, T. Matsuda and J. K. Kim. Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics (AISTATS 2020)., 2020.
A Stein goodness-of-fit test for directional distributions. [Proceedings Website]
W. Xu and T. Matsuda. Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics (AISTATS 2020)., 2020.
A unified statistically efficient estimation framework for unnormalized models. [Proceedings Website]
M. Uehara, T. Kanamori, T. Takenouchi and T. Matsuda. Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics (AISTATS 2020)., 2020.
Timing of phase amplitude coupling in the temporal pole is essential for neuronal and functional maturation of audiovisual integration in adolescence. [Journal Website]
T. Ohki*, T. Matsuda*, A. Gunji, Y. Takei, R. Sakuma, Y. Kaneko, M. Inagaki, T. Hanakawa, K. Ueda, M. Fukuda and K. Hiraki. Brain and Behavior, e01635, 2020.
Game-theoretic derivation of upper hedging prices of multivariate contingent claims and submodularity. [Journal Website]
T. Matsuda and A. Takemura. Japan Journal of Industrial and Applied Mathematics, 37, 213--248, 2020.
Estimation of Non-Normalized Mixture Models. [Proceedings Website]
T. Matsuda and A. Hyvarinen. Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics (AISTATS 2019)., 2019.
Harmonic Bayesian prediction under alpha-divergence. [Journal Website]
Y. Maruyama, T. Matsuda and T. Onishi. IEEE Transactions on Information Theory, 65, 5352--5366, 2019.
Empirical Bayes matrix completion. [Journal Website] [MATLAB code]
T. Matsuda and F. Komaki. Computational Statistics & Data Analysis, 137, 195--210, 2019.
Improved loss estimation for a normal mean matrix. [Journal Website] [METR]
T. Matsuda and W. E. Strawderman. Journal of Multivariate Analysis, 169, 300--311, 2019.
A note on improving on a vector of coordinate-wise estimators of non-negative means via shrinkage. [Journal Website]
Y. T. Chang, T. Matsuda and W. E. Strawderman. Statistics & Probability Letters, 153, 143--150, 2019.
Minimax estimation of quantum states based on the latent information priors. [Journal Website]
T. Koyama, T. Matsuda and F. Komaki. Entropy, 19, 618, 2017.
Sexual dimorphisms of mRNA and miRNA in human/murine heart disease. [Journal Website]
M. Tsuji, T. Kawasaki, T. Matsuda, S. Gojo and J. Takeuchi. PLOS ONE, 12, e0177988, 2017.
Multivariate time series decomposition into oscillation components. [Journal Website] [MATLAB code]
T. Matsuda and F. Komaki. Neural Computation, 29, 2055--2075, 2017.
A point process modeling approach for investigating the effect of online brain activity on perceptual switching. [Journal Website]
T. Matsuda, K. Kitajo, Y. Yamaguchi and F. Komaki. NeuroImage, 152, 50--59, 2017.
Time series decomposition into oscillation components and phase estimation. [Journal Website] [MATLAB code]
T. Matsuda and F. Komaki. Neural Computation, 29, 332--367, 2017.
Pitman closeness properties of Bayes shrinkage procedures in estimation and prediction. [Journal Website]
T. Matsuda and W. E. Strawderman. Statistics & Probability Letters, 119, 21--29, 2016.
Pitman closeness properties of point estimators and predictive densities with parametric constraints. [Journal Website]
T. Matsuda and W. E. Strawderman. Statistics & Probability Letters, 116, 101--106, 2016.
Singular value shrinkage priors for Bayesian prediction. [Journal Website]
T. Matsuda and F. Komaki. Biometrika, 102, 843--854, 2015.
A new geometric integration approach based on local invariants. [Journal Website]
T. Matsuda and T. Matsuo. JSIAM Letters, 5, 37--40, 2013.
Discussion of "Akaike Memorial Lecture 2022: Identifiability of latent-variable and structural-equation models: from linear to nonlinear." [Journal Website]
T. Matsuda. Annals of the Institute of Statistical Mathematics, accepted.