Publications


Journal papers and refereed proceedings (peer reviewed)

  1. Kuroda, M, Geng, Z. and Sakakihara, M. (2015). Improving the vector epsilon acceleration for the EM algorithm using a re-starting procedure. Computational Statistics, 30, 1051 - 1077.[download]
  2. Mori, M., Kuroda, M., Izuka, M. and Sakakihara, Y. (2014). Performance of acceleration of ALS algorithm in nonlinear PCA. Proceedings of COMPSTAT 2014 , 257-263.
  3. Kuroda, M., Mori, Y., Iizuka, M and Sakakihara, M. (2013). Alternating least squares in nonlinear principal components. WIREs Computational Statistics, 5, 456 - 464. [download]
  4. Kuroda, M., Hashiguchi, H., Nakagawa, S.  and Geng, Z. (2013). MCMC using Markov bases for computing p-values in decomposable log-linear models.  Computational Statistics, 28, 831- 850. [download]
  5. Kuroda, M., Sakakihara, M., Mori, Y. and iizuka, M. (2012). Two-stage acceleration for non-linear PCA. Proceedings of COMPSTAT2012, pp. 461-471. [draft]
  6. Kuroda, M., Mori, Y., Iizuka, M and Sakakihara, M. (2012). Acceleration of convergence of the alternating least squares algorithm for nonlinear principal components analysis. In Principal Component Analysis (Sanguansat, P. (Ed.)), InTech Publications, 129-144. ISBN 978-953-51-0195-6. [download]
  7. Kuroda, M., Iizuka, M., Mori, Y.  and Sakakihara, M. (2011). Principal components based on a subset of qualitative variables and its accelerated computational algorithm. In the Proceedings of the ISI-2011 in Dublin. [download].
  8. Kuroda, M., Mori, Y., Iizuka, M. and Sakakihara, M. (2011). Acceleration of the alternating least squares algorithm for principal components analysis. Computational Statistics and Data Analysis, 55, 143-153. [download]
  9. Kuroda, M., Mori, Y. Iizuka, M. and Sakakihara, M. (2010). Improvement of acceleration of the ALS Algorithm using the vector algorithm . Proceedings of COMPSTAT'2010 (full contribution, edited by Lechevallier, Yves; Saporta, Gilbert), Psysica-Verlag, Heidelberg, 1239-1246.
  10. Kuroda, M., Hashiguchi, H. and Nakagawa, S. (2010). Computing p-values in conditional independence models for a contingency table.  Computational Statistics, 25, 57-70. [preprint]
  11. Kuroda, M., Sakakihara, M. and Geng, Z. (2008). Acceleration of the EM and ECM algorithms using the Aitken delta^2 method for log-linear models with partially classified data. Statistics and Probability Letters, 78, 2332-2338.[download]
  12. Wang, M., Kuroda, M., Sakakihara, M. and Geng, Z. (2008). Acceleration of the EM algorithm using the vector epsilon algorithm, Computational Statistics, 23, 469-486. [preprint]
  13. Sakakihara, M. and Kuroda, M. (2008). Convergence of componentwise Aitken delta^2 acceleration of the EM algorithm. COMPSTAT 2008: Proceedings in Computational Statistics (full contribution, edited by Paula Brito), Psysica-Verlag, Heidelberg, 597-903.
  14. Kuroda, M. and Sakakihara, M. (2006). Accelerating the convergence of the EM algorithm using the vector epsilon algorithm, Computational Statistics and Data Analysis, 51, 1549-1561. [download]
  15. Kuroda, M. and Sakakihara, M. (2006). Acceleration of the EM and ECM algorithms for log-linear models with missing data. COMPSTAT 2006: Proceedings in Computational Statistics (full contribution, edited by Alfredo, Rizzi and Maurizio Vichi), Psysica-Verlag, Heidelberg, 591-598. [download]
  16. Sakakihara, M. and Kuroda, M. (2005). Improving convergence rate of EM algorithm via component wise Aitken delta^2 acceleration, Information 8, 823-828.
  17. Kuroda, M. (2005). Data augmentation algorithm for graphical models with missing data. Neural Network World, 15, 343-350.[download]
  18. Kuroda, M. (2004). Parameter estimation using Bayesian sequential learning for latent class models (in Japanese). Bulletin of The Computational Statistics Society of Japan, 17, 9-20.
  19. Kuroda, M. (2004). Data augmentation algorithm for graphical models with missing data. COMPSTAT 2004: Proceedings in Computational Statistics (full contribution, edited by Jaromir Antoch), Psysica-Verlag, Heidelberg, 1361-1368. [download]
  20. Kuroda, M. and Geng, Z. (2002). Bayesian inference for categorical data with misclassification errors, in ADVANCES IN STATISTICS, COMBINATORICS AND RELATED AREAS, (edited by Chandra Gulati, Yan-Xia Lin, John Rayner and Satya Mishra), World Scientific Publishing, 143 - 151.  [download]
  21. Kuroda, M., Geng, Z. and Niki, N. (2001). Bayesian sequential learning from incomplete data on decomposable graphical models, Journal of the Japanese Society of Computational Statistics, 14, 11-29. [download]
  22. Kuroda, M. and Geng, Z. (1999). Minimum information updating with specified marginals in probabilistic expert systems, Journal of the Japanese Society of Computational Statistics, 12, 41-50. [download]

Chapters of Books


Dr. Theses

Kuroda, M. (1999). Parameter estimation from incomplete categorical data in graphical models, Tokyo University of Science.

 Proceedings

  1. Kuroda, M. (2014). An initial value selection method of the EM algorithm for mixture models. Proccedings of Kyoto International Conference on Modern Statistics in the 21st Century, ??.
  2. Kuroda, M. (2013). Acceleration of the EM algorithm to mixture models. Proceedings of Ishigaki International Conference on Modern Statistics Theories, Practices, and Education in the 21st Century, 10.
  3. Kuroda, M., Mori, Y., Iizuka, M. and Sakakihara, M. (2011). Variable selection in principal components analysis of qualitative data using the accelerated ALS algorithm. Proceedings of the 7th conference of Asian Regional Section of IASC, 83.
  4. Sakakihara, M. and Kuroda, M (2011). King-Werner method for EM algorithm. Proceedings of the 7th conference of Asian Regional Section of IASC, 84.
  5. Sakakihara, M. and Kuroda, M (2010). Acceleration of convergence for the alternating least squares iteration. 4th CSDA International Conference on Computational and Financial Econometrics.
  6. Kuroda, M. Hashiguchi, H. and Nakagawa, S. (2008). Random table generation for decomposable log-linear models by Markov basis. Abstracts of Workshop on Computational Algebraic Statistics, Theories and Applications, 24 - 25.
  7. Kuroda, M., Mori, Y., Iizuka, M. and Sakakihara, M. (2008). Accerelation of convergence of the alternating least squares algorithm for principal component analysis. Program & Abstracts IASC 2008, 172-172.@@
  8. Kuroda, M. Hashiguchi, H. and Nakagawa, S. (2007). Computing of p-values for conditional independence models for a four-way contingency table. Proceedings of the Ninth Japan-China Symposium on Statistics, 125 – 130.
  9. Sakakihara, M., and Kuroda, M. (2007). Componentwise acceleration of EM-algorithm. Proceedings of the Ninth Japan-China Symposium on Statistics. 225 – 228.
  10. Kuroda, M. and Sakakihara, M. (2005). Accelerating the convergence of the EM algorithm using the vector epsilon algorithm, Proceedings of the 5th IASC Asian Conference on Statistical Computing, 101-104.
  11. Sakakihara, M. and Kuroda, M. (2004). Improving convergence rate of the EM algorithm, Proceedings of the Third International Conference on INFORMATION, International Information Institute, 347-350.
  12. Kuroda, M. (2002). Data augmentation algorithm in the analysis of contingency tables with misclassification, Proceedings in Computational Statistics 2000, short communications and posters in CD-ROM.
  13. Kuroda, M. (2000). Bayesian estimation of misclassified categorical data, Proceedings of the seventh Japan and China Symposium on Statistics, 301-304.
  14. Yamaguchi, K., Nakagawa, S., Kuroda, M. and Watanabe, M. (2000). MCMC and the latent class analysis, Proceedings of the seventh Japan and China Symposium on Statistics, 197-200.
  15. Kuroda, M. (2000). Contingency table analysis with misclassification errors by MCMC, Proceedings in Computational Statistics 2000, short communications and posters, 47-48.
  16. Yamaguchi, K., Nakagawa, S., Kuroda, M. and Watanabe, M. (2000). Deriving sampling distributions of test statistics for the latent class model by Markov chain Monte Carlo, Proceedings in Computational Statistics 2000, short communications and posters, 127-128.
  17. Kuroda, M., Niki, N. and Geng, Z. (1998). Estimation of latent parameters by Bayesian sequential learning, Conference papers, 3rd conference on Statistical Computing of the ASIAN REGIONAL SECTION, 233-244.
  18. Kuroda, M. and Geng, Z. (1997). Latent model analysis by Bayesian sequential learning, Proceedings of the Sixth China and Japan Symposium on Statistics, 111-114.
  19. Kuroda, M. (1995). Estimation in graphical models with given marginals, Bulletin of the 50th Session of the International Statistical Institute, Contributed Papers, 649-650.
  20. Geng, Z., Kuroda, M, Asano, Ch. and Ichimura, M. (1995). Partial imputation of missing data in graphical models, Bulletin of the 50th Session of the International Statistical Institute, Contributed Papers, 1454-1455.
  21. Geng, Z., Asano, Ch., Ichimura, M. and Kuroda, M.(1995). Conditional double sampling schemes for quality control with miscalssifications, Proceedings of International Conference on Statistical Methods and Statistical Computing for Quality and Productivity Improvement, 835-841.
  22. Kuroda, M., Geng, Z. and Ichimura, M. (1994). Updating of probabilities with specified marginals in probabilistic expert systems, Proceedings of the Fifth China and Japan Symposium on Statistics, 131-134.
  23. Geng, Z, Kuroda, M. and Asano, Ch. (1994). Bayesian sequential updating on decomposable models, Proceedings of the Fifth China and Japan Symposium on Statistics, 82-85.
  24. Kuroda, M. and Ichimura, M. (1993). Runs in a sequence of autocorrelated normal numbers, Proceedings of the Asian Conference on Statistical Computing, 108-111.