Shinto EGUCHI
Professor, Learning and Inference Group, Department of Mathematical Analysis and Statistical Inference;
Statistical Genome Diversity Research Group, Prediction and Knowledge Discovery Research Center
Phone: +81-50-5533-8500
E-mail: eguchi
Personal
Homepage:		 http://www.ism.ac.jp/~eguchi/
Education: BA: Department of Mathematics, Osaka University, March 1977
MA: Department of Mathematical Sciences, March 1979
Degree: Doctor of Science, Hiroshima University, 1984, Title of Doctoral Thesis: A study on contrast functionals and its applications to statistical inference.
Employment: Assistant Professor, Hiroshima University, January 1984
Associate Professor, Shimane University, April 1988
Associate Professor, Institute of Statistical Mathematics, 1995
Professor, Institute of Statistical Mathematics, 1996-
Professor, Department of Mathematical Analysis and Statistical Inference; Prediction and Knowledge Discovery Research Center, Institute of Statistical Mathematics, 2005-
Research
Fields:		 Information geometry, Statistical inference, Statistical machine learning , Robust statistics, Satistical pattern recognition, Bioinformatics, Finantial engineering
Research
Themes:		 1. Local likelihood: The method bases on mounting a kernel function into the likelihood in order to get local information over the data space.
2. Selection bias: All the possible situations caused from observations is studyed in term of the infomation geometric method.
3. Robust statistics: A calss of Bregman U-divergences leads to a special structure from an information-geometric point of view. The structure helps to robustify the conventinal procedure of PCA, ICA, finite mixture model, discriminant analysis and so forth.
4. Bioinformatics: Novel statistical metods are proposed for the prediction and association study from gene related data sets by the use of robust model-based clustering , boosting learning algorithms and kernel methods.
5. Finance engineering. Statistical methods are challenged to be exploited to solve practical problems in finance data.

Selected Papers
(1) S. Eguchi (1983): Second order efficiency of minimum contrast estimators in a curved exponential family, Ann. Statist., 11, 793-803.
(2) H. Wakaki, S. Eguchi and Y. Fujikoshi (1990): A class of tests for general covariance structure, J. Multivariate Analysis, 32, 313-325.
(3) M. Matuura and S. Eguchi (1990): Estimation of gene frequency and test for Hardy-Weinberg equilibrium in the HLA system, Environmental Health Perspectives, 87, 149-155.
(4) S. Eguchi and M. Matuura (1990): Testing the Hardy-Weinberg equilibrium in the HLA system, Biometrics, 46, 415-426.
(5) S. Eguchi (1992): Geometry of minimum contrast, Hiroshima Math. J., 22, 631-647.
(6) T. Amisaki and S. Eguchi (1995): Pharmacokinetic parameter estimations by minimum relative entropy method, J. Pharmacokinetics and Biopharmaceutics, 23, 479-494.
(7) I. Higuchi and S. Eguchi (1998): The influence function of principal component analysis by self-organizing rule, Neural Computation, 10, 1435-1444.
(8) S. Eguchi and J. Copas (1998): A class of local likelihood methods and near-parametric asymptotics, J. Royal Statist. Soc. B, 60, 709-724.
(9) T. Amisaki and S. Eguchi (1999): A comparison of methods for estimating individual pharmacokinetic parameters, J. Pharmacokinetics and Biopharmaceutics, 27, 103-121.
(10) H. Kamiya and S. Eguchi (2001): A class of robust principal component vectors, J. Multivariate Analysis, 77, 239-269.
(11) J. Copas and S. Eguchi (2001): Local sensitivity approximation for selectivity bias, J. Royal Statistical Society B, 63, 871-895.
(12) S. Eguchi and J. Copas (2002): A class of logistic-type discriminant functions, Biometrika, 89, 1-22.
(13) M. Minami and S. Eguchi. (2002): Robust blind source separation by beta-divergence, Neural Computation, 14, 1859-1886.
(14) H. Fujisawa, S. Eguchi, M. Ushijima, S. Miyata, Y. Miki, T. Muto and M. Matsuura (2004): Genotyping of single nucleotide polymorphism using model-based clustering, Bioinformatics, 20, 718-726.
(15) T. Takenouchi and S. Eguchi (2004): Robustifying AdaBoost by adding the naive error rate, Neural Computation, 16, 767-787.
(16) N. Murata, T. Takenouchi, T. Kanamori and S. Eguchi (2004): Information geometry of U-Boost and Bregman divergence, Neural Computation, 16, 1437-1481.
(17) I. Higuchi and S. Eguchi (2004): Robust principal component analysis with adaptive selection for tuning parameters, J. Machine Learning Research, 5, 453-471.
(18) M. Henmi and S. Eguchi (2004): A paradox concerning nuisance parameters and projected estimating functions, Biometrika, 91, 929-941.
(19) M. Matuura and S. Eguchi (2005): Modeling late entry bias in survival analysis, Biometrics, 61, 559-566.
(20) J. Copas and S. Eguchi (2005): Local model uncertainty and incomplete data bias (with discussion), J. Royal Statistical Society B, 67, 459-512.
(21) R. Nishii and S. Eguchi. (2005): Supervised image classification by contextual AdaBoost based on posteriors in neighborhoods, IEEE Tran. on Geoscience and Remote Sensing, 43, 2547-2554.
(22) M. Kawakita, M. Minami, S. Eguchi and C. E. Lennert-Cody (2005): An introduction to the predictive technique AdaBoost with a comparison to generalized additive models, Fisheries Research, 76, 328-343.
(23) M.N.H. Mollah, M. Minami and S. Eguchi (2006): Exploring latent structure of mixture ICA models by the minimum beta-divergence method, Neural Computation, 18, 166-190.
(24) T. Fushiki, H. Fujisawaand S. Eguchi (2006): Identification of biomarkers from mass spectrometry data using a "common" peak approach, BMC Bioinformatics, 7:358.
(25) S. Eguchi and J. Copas (2006): Interpreting Kullback-Leibler divergence with the Neyman-Pearson lemma, J. Multivariate Analysis, 97, 2034-2040.
(26) R. Nishii and S. Eguchi (2006): Image classification based on Markov random field models with Jeffreys divergence, J. Multivariate Analysis, 97, 1997-2008.
(27) M. Henmi, J. Copas and S. Eguchi (2007): Confidence intervals and P-values for meta analysis with publication bias, Biometrics, 63, 475-482.
(28) T. Kanamori, T. Takenouchi, S. Eguchi and N. Murata (2007): Robust Loss Functions for Boosting, Neural Computation, 19, 2183-2244.
(29) M. Henmi, R. Yoshida and S. Eguchi (2007): Importance sampling via the estimated sampler, Biometrika, 94, 985-991.
(30) T. Takenouchi, S. Eguchi, N. Murata and T. Kanamori (2008): Robust boosting algorithm against mislabeling in multi-class problems, Neural Computation 20, 6, 1596-1630.
(31) H. Fujisawa and S. Eguchi. Robust parameter estimation with a small bias against heavy contamination. J. Multivariate Analysis, 99, 9 (2008) 2053-2081.
(32) M. Kawakita and S. Eguchi. Boosting method for local learning in statistical pattern recognition. Neural Computation, 20, 11 (2008) 2792-2838.
(33) H. Fujisawa, Y. Horiuchi, Y. Harushima, T. Takada, S. Eguchi, T. Mochizuki, T. Sakaguchi, T. Shiroishi, and N. Kurata. SNEP: Simultaneous detection of nucleotide and expression polymorphisms using Affymetrix GeneChip. BMC Bioinformatics 10 (2009) 131.
(34) S-Y. Huang, Y-R. Yeh and S. Eguchi. Robust kernel principal component analysis. Neural Computation, 21, 11 (2009) 3179-3213.
(35) S. Eguchi. and S. Kato. Entropy and divergence associated with power function and the statistical application.Entropy 12, 2 (2010) 262-274.
(36) N. H. Mollah, N. Sultana, M. Minami and S. Eguchi. Robust extraction of local structures by the minimum beta-divergence method. Neural Networks 23, 2 (2010) 226-238.
(37) J. Copas and S. Eguchi. Likelihood for statistically equivalent models. J. Royal Statistical Society B, 72, 2 (2010) 193-217.
(38) O. Komori, S. Eguchi. A boosting method for maximizing the partial area under the ROC curve. BMC Bioinformatics (2010) 11:314.

Membership of Academic Societies
Japan Statistical Society, Japan Mathematical Society, Japan Biometric Society, Japan Neural Network Society, Royal Statistical Society

Professional Services
Program Committee (1998-2000) of Japan Statistical Society, Associate Editor of JJSS (1998-2002). Organizing committee of Bernoulli 2000 Conference on Neural Networks and Learning. Program committee of Fourth International symposium on independent component analysis 2003. Program committee of Workshop on Self-organizing Map 2003.Program committee of Sixth International symposium on independent component analysis 2005. Chair of program committee of 2nd International Symposium on Information Geometry and its Applications, 2005. Boad meeting member of Japan Statistical Society (2008- ).

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