| [p50] |
Boosting method for local learning in statistical
pattern recognition. M. Kawakita and S. Eguchi. To appear in
Neural Computation, 2008 [preprint] |
| [p49] |
Robust parameter estimation with a small
bias against heavy contamination. H. Fujisawa and S. Eguchi. To apper in J. Multivariate Analysis, 2008. [preprint] |
| [p48] |
Robust boosting algorithm against mislabeling
in multi-class problems. T. Takenouchi, S. Eguchi, N. Murata and
T. Kanamori. To appear in Neural Computation, 2008. [abst] [preprint] |
| [p47] |
Asymptotical improvement of maximum likelihood
estimators on Kullback-Leibler loss. S. Eguchi and T. Yanagimoto. To appear
in J. Statist. Plan. Infer, 2008. [abst] [preprint] |
| [p46] |
Common peak approach using mass spectrometry
data sets for predicting the effects of anticancer
drugs on breast cancer. M. Ushijima, S. Miyata, S. Eguchi, M. Kawakita,
M. Yoshimoto, T. Iwase, F. Akiyama, G. Sakamoto,
K. Nagasaki, Y. Miki, T. Noda, Y. Hoshikawa
and M. Matsuura. Cancer Informatics, 3 (2007) 285-293. [abst] [preprint] |
| [p45] |
Importance sampling via the estimated sampler.
M. Henmi, R. Yoshida and S. Eguchi. Biometrika 94, 4, 985-991 (2007). [abst] [preprint] |
| [p44] |
Identifying haplotype block structure by
using ancestor-derived model. H. Fujisawa, M. Isomura, S. Eguchi, M.
Ushijima, S. Miyata, Y. Miki, M. Matsuura.
J. Human Genetics 52 (9) (2007) 738-746. [abst] [preprint] |
| [p43] |
Robust loss functions for boosting. T. Kanamori, T. Takenouchi, S. Eguchi and
N. Murata. Neural Computation 19 (2007) 2183-2244. [abst] [preprint] |
| [p42] |
Confidence intervals and P-values for meta
analysis with publication bias. M. Henmi, J. Copas and S. Eguchi. Biometrics 63 (2007) 475-482. [abst] [preprint] |
| [p41] |
Robust prewhitening for ICA by minimizing
beta-divergence and its application
to FastICA. M. N. H. Mollah, M. Minami and S. Eguchi.
Neural Processing Letters 25 (2007) 91-110. [abst] [preprint]
|
| [p40] |
GroupAdaBoost: accurate prediction and selection
of important genes. T. Takenouchi, M. Ushijima and S.Eguchi.
IPSJ Transactions on Bioinformatics (2007) 3, 1-8. [abst] [preprint] |
| [p39] |
Identification of biomarkers from mass spectrometry
data using a "common" peak
approach. T. Fushiki, H. Fujisawa and S. Eguchi.
BMC Bioinformatics (2006) 7:358. [abst] [preprint] |
| [p38] |
Interpreting Kullback-Leibler divergence
with the Neyman-Pearson lemma. S. Eguchi and J. Copas. J. Multivariate Analysis 97 (2006) 2034-2040. [abst] [preprint] |
| [p37] |
Image classification based on Markov random
field models with Jeffreys divergence. R. Nishii and S. Eguchi. J. Multivariate Analysis 97 (2006) 1997-2008. [abst] [preprint] |
| [p36] |
Exploring latent structure of mixture ICA
models by the minimum beta-divergence
method. M. N. H. Mollah, M. Minami and S.
Eguchi. Neural Computation 18 (2006) 166-190. [abst] [preprint] |
| [p35] |
Robust estimation in the normal mixture model. H. Fujisawa and S. Eguchi. J. Statist. Plan. Infer., 136, (2006) 3989-4011. [abst] [preprint] |
| [p34] |
Information geometry and statistical pattern
recognition. S. Eguchi. Sugaku Expositions, Amer. Math. Soc, 19 (2006) 197-216. [abst] [preprint] |
| [p33] |
Local likelihood density estimation when
the bandwidth is large. B. U. Park, Y. K. Lee, T. Y. Kim, C. Park
and S. Eguchi. J. Statist. Plan. Infer., 136 (2006) 839-859. [abst] [preprint] |
| [p32] |
An introduction to the predictive technique
AdaBoost with a comparison to generalized
additive models. M. Kawakita, M. Minami, S. Eguchi and C.
E. Lennert-Cody. Fisheries Research 76 (2005) 328-343 [abst] [preprint] |
| [p31] |
Supervised image classification by contextual
AdaBoost based on posteriors in neighborhoods. R. Nishii and S. Eguchi. IEEE Tran. on Geoscience and Remote Sensing, 43 (2005) 2547-2554. [abst] [preprint] |
| [p30] |
Local model uncertainty and incomplete data
bias (with discussion). J. Copas and S. Eguchi.
J. Royal Statistical Society B 67 (2005) 459-512. [abst] [preprint] |
| [p29] |
Modeling late entry bias in survival analysis. M. Matsuura and S. Eguchi.
Biometrics 61 (2005) 559-566. [abst] [preprint] |
| [p28] |
Local likelihood regression of acoustic logging
data with adaptive selection of multiple
bandwidth. S. Watanabe, M. Minami and
S. Eguchi. Butsuri-Tansa 57 (2004) 535-544. [abst] [preprint] |
| [p27] |
A paradox concerning nuisance parameters
and projected estimating functions. M. Henmi and S. Eguchi. Biometrika 91 (2004) 929-941. [abst] [preprint] |
| [p26] |
Robust principal component analysis with
adaptive selection for tuning parameters. I. Higuchi and S. Eguchi. J. Machine Learning Research 5 (2004) 453-471. [abst] [preprint] |
| [p25] |
Information geometry of U-Boost and Bregman divergence. N. Murata, T. Takenouchi, T. Kanamori
and S. Eguchi. Neural Computation 16 (2004) 1437-1481. [abst] [preprint] |
| [p24] |
Genotyping of single nucleotide polymorphism
using model-based clustering. H. Fujisawa, S. Eguchi, M. Ushijima, S.
Miyata, Y. Miki, T. Muto and M. Matsuura.
Bioinformatics 20 (2004) 718-726. [abst] [preprint] |
| [p23] |
Robustifying AdaBoost by adding the naive
error rate. T. Takenouchi and S. Eguchi. Neural Computation 16 (2004) 767-787. [abst] [preprint] |
| [p22] |
Local likelihood method: a bridge over parametric
and nonparametric regression. S. Eguchi, T-Y. Kim and B. U. Park.
J. Nonparametric Statistics 15 (2003) 665-683. [abst] [preprint] |
| [p21] |
Robust blind source separation by beta-divergence. M. Minami and S. Eguchi, Neural Computation 14 (2002) 1859-1886. [abst] [preprint] |
| [p20] |
A class of logistic-type discriminant functions. S. Eguchi and J. Copas, Biometrika 89 (2002) 1-22. [abst] [preprint] |
| [p19] |
Local sensitivity approximation for selectivity
bias. J. Copas and S. Eguchi, J. Royal Statistical Society B, 63 (2001) 871-895. [abst] [preprint] |
| [p18] |
A class of robust principal component vectors. H. Kamiya and S. Eguchi, J. Multivariate Analysis 77 (2001) 239-269. [abst] [preprint] |
| [p17] |
Recent developments in discriminant analysis
from an information geometric point
of view. J. Korean Statist. Soc. 30 (2001) 247-264. S. Eguchi and
J. Copas. [abst] [preprint] |
| [p16] |
A comparison of methods for estimating individual
pharmacokinetic parameters. T. Amisaki and S. Eguchi, J. Pharmacokinetics and Biopharmaceutics, 27 (1999) 103-121. [abst] [preprint] |
| [p15] |
A class of local likelihood methods and near-parametric
asymptotics. S. Eguchi and J. Copas, J. Royal Statistical Society B 60 (1998) 709-724. [abst] [preprint] |
| [p14] |
The influence function of principal component
analysis by self-organizing rule. I. Higuchi and S. Eguchi, Neural Computation 10 (1998) 1435-1444. [abst] [preprint] |
| [p13] |
Pharmacokinetic parameter estimations by
minimum relative entropy method. T. Amisaki and S. Eguchi, J. Pharmacokinetics and Biopharmaceutics 23 (1995) 479-494. [abst] [preprint] |
| [p12] |
A further discussion of second order efficiency
for estimation. S. Eguchi. Questio 17 (1993) 347-364. [abst] [pdf] |
| [p11] |
Geometry of minimum contrast. S. Eguchi. Hiroshima Math. J. 22 (1992) 631-647.[pdf] |
| [p10] |
The projection method for accelerated life
test model in bivariate exponential
distributions. S. Eguchi. Hiroshima Math. J. 22 (1992) 185-193. [pdf] |
| [p09] |
A geometric look at nuisance parameter effect
of local powers in testing hypothesis. S. Eguchi. Ann. Inst. Statist. Math. 43 (1991) 245-260. [abst] [pdf] |
| [p08] |
Testing the Hardy-Weinberg equilibrium in
the HLA system. S. Eguchi and M. Matsuura, Biometrics 46 (1990) 415-426. [abst] [pdf] |
| [p07] |
Estimation of gene frequency and test for
Hardy-Weinberg equilibrium in the HLA
system. M. Matsuura and S. Eguchi, Environmental Health Perspectives 88 (1990) 149-155. [abst] [pdf] |
| [p06] |
A class of tests for general covariance structure. H. Wakaki, S. Eguchi and Y. Fujikoshi. J. Multivariate Analysis 32 (1990) 313-325. [abst] [pdf] |
| [p05] |
A unified approach to improper solutions
of maximum likelihood estimates. S. Eguchi. J. Japan Statist. Soc. 19 (1989) 67-82. [abst] [pdf] |
| [p04] |
A projection method of estimation for a subfamily
of exponential families. S. Eguchi. Ann. Inst. Statist. Math. 38 A (1986) 385-398. [pdf] |
| [p03] |
A differential geometric approach to statistical
inference on the basis of contrast
functionals. S. Eguchi. Hiroshima Math. J. 15 (1985) 341-391. [abst] [pdf] |
| [p02] |
A characterization of second order efficiency
in a curved exponential family. S. Eguchi. Ann. Inst. Statist. Math.36 A (1984) 199-206. [pdf] |
| [p01] |
Second order efficiency of minimum contrast
estimators in a curved exponential
family. S. Eguchi. Ann Statist. 11 (1983) 793-803. [abst] [pdf] |
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