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Akimichi Takemura

Akimichi Takemura

D-Index & Metrics

Mathematics

D-Index
31
Citations
3572
World Ranking
3364
National Ranking
55

Overview

Akimichi Takemura is affiliated with Shiga University in Japan and has contributed to research primarily within the fields of Mathematics and Environmental Science. Their scholarly work extends across subfields including Statistics and Probability, Environmental Engineering, Applied Mathematics, Artificial Intelligence, and Computational Mechanics.

Their main research topics cover a range of themes such as Soil Geostatistics and Mapping, Statistical Methods and Inference, Point Processes and Geometric Inequalities, Remote Sensing and LiDAR Applications, Bayesian Methods and Mixture Models, Advanced Numerical Analysis Techniques, and Machine Learning and Algorithms.

Takemura has published work in several venues, with frequent publications appearing in:

  • arXiv (Cornell University)
  • Journal of Multivariate Analysis
  • Japanese Journal of Statistics and Data Science

Collaborations have included partnerships with authors such as:

  • Yuzo Maruyama
  • Satoshi Kuriki
  • Jonathan Taylor

Recent papers authored or co-authored by Takemura include:

  • The volume-of-tube method for Gaussian random fields with inhomogeneous variance, 2021, Journal of Multivariate Analysis
  • The volume-of-tube method for Gaussian random fields with inhomogeneous variance, 2021, arXiv (Cornell University)
  • Non-minimaxity of debiased shrinkage estimators, 2023, arXiv (Cornell University)
  • Non-minimaxity of debiased shrinkage estimators, 2023, Japanese Journal of Statistics and Data Science
  • A new perspective on dominating the James-Stein estimator, 2025, arXiv (Cornell University)

Best Publications

  • An Asymptotically Optimal Bandit Algorithm for Bounded Support Models.

    Junya Honda;Akimichi Takemura

  • Markov Bases in Algebraic Statistics

    Satoshi Aoki;Hisayuki Hara;Akimichi Takemura

  • Validity of the expected Euler characteristic heuristic

    Jonathan Taylor;Akimichi Takemura;Robert J. Adler

  • Minimal Basis for a Connected Markov Chain over 3 x 3 x K Contingency Tables with Fixed Two-Dimensional Marginals

    Satoshi Aoki;Akimichi Takemura

  • Some characterizations of minimal Markov basis for sampling from discrete conditional distributions

    Akimichi Takemura;Satoshi Aoki

  • An orthogonally invariant minimax estimator of the covariance matrix of a multivariate normal population

    Akimichi Takemura

  • Tensor Analysis of ANOVA Decomposition

    Akimichi Takemura

  • On connectivity of fibers with positive marginals in multiple logistic regression

    Hisayuki Hara;Akimichi Takemura;Ruriko Yoshida

  • Holonomic gradient descent and its application to the Fisher-Bingham integral

    Hiromasa Nakayama;Kenta Nishiyama;Masayuki Noro;Katsuyoshi Ohara

  • WHY DO NONINVERTIBLE ESTIMATED MOVING AVERAGES OCCUR

    T. W. Anderson;Akimichi Takemura

  • Optimality of Thompson Sampling for Gaussian Bandits Depends on Priors

    Junya Honda;Akimichi Takemura

  • ON THE EQUIVALENCE OF THE TUBE AND EULER CHARACTERISTIC METHODS FOR THE DISTRIBUTION OF THE MAXIMUM OF GAUSSIAN FIELDS OVER PIECEWISE SMOOTH DOMAINS

    Akimichi Takemura;Satoshi Kuriki

  • The holonomic gradient method for the distribution function of the largest root of a Wishart matrix

    Hiroki Hashiguchi;Yasuhide Numata;Nobuki Takayama;Akimichi Takemura

  • Defensive forecasting

    Vladimir Vovk;Akimichi Takemura;Glenn Shafer

  • Tail probabilities of the maxima of multilinear forms and their applications

    Satoshi Kuriki;Akimichi Takemura

  • Markov chain Monte Carlo exact tests for incomplete two-way contingency tables

    Satoshi Aoki;Akimichi Takemura

  • An asymptotically optimal policy for finite support models in the multiarmed bandit problem

    Junya Honda;Akimichi Takemura

  • Empirical characteristic function approach to goodness-of-fit tests for the Cauchy distribution with parameters estimated by MLE or EISE

    Muneya Matsui;Akimichi Takemura

  • Goodness-of-fit tests for symmetric stable distributions—Empirical characteristic function approach

    Muneya Matsui;Akimichi Takemura

  • Inadmissability of non-order-preserving orthogonally invariant estimators of the covariance matrix in the case of Stein's loss

    Yo Sheena;Akimichi Takemura

  • Non-asymptotic analysis of a new bandit algorithm for semi-bounded rewards

    Junya Honda;Akimichi Takemura

  • Weights of $overline{\chi}{}\sp 2$ distribution for smooth or piecewise smooth cone alternatives

    Akimichi Takemura;Satoshi Kuriki

  • Holonomic Gradient Descent and its Application to Fisher-Bingham Integral

    Tomonari Sei;Nobuki Takayama;Akimichi Takemura;Hiromasa Nakayama

  • Holonomic gradient method for the distribution function of the largest root of a Wishart matrix

    Hiroki Hashiguchi;Yasuhide Numata;Nobuki Takayama;Akimichi Takemura

Frequent Co-Authors

Glenn Shafer
Glenn Shafer Rutgers, The State University of New Jersey
Hyundong Shin
Hyundong Shin Kyung Hee University
Takayuki Hibi
Takayuki Hibi Osaka University
Jonathan Taylor
Jonathan Taylor Stanford University
Taiji Suzuki
Taiji Suzuki University of Tokyo
T. W. Anderson
T. W. Anderson Stanford University
Robert J. Adler
Robert J. Adler Technion – Israel Institute of Technology

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