 | 2011 |
| 21 |  | Osamu Komori,
Shinto Eguchi:
Boosting Learning Algorithm for Pattern Recognition and Beyond.
IEICE Transactions 94-D(10): 1863-1869 (2011) |
| 2010 |
| 20 |  | Osamu Komori,
Shinto Eguchi:
A boosting method for maximizing the partial area under the ROC curve.
BMC Bioinformatics 11: 314 (2010) |
| 19 |  | Md. Nurul Haque Mollah,
Shinto Eguchi:
Robust QTL analysis by minimum beta-divergence method.
IJDMB 4(4): 471-485 (2010) |
| 18 |  | Md. Nurul Haque Mollah,
Nayeema Sultana,
Mihoko Minami,
Shinto Eguchi:
Robust extraction of local structures by the minimum beta-divergence method.
Neural Networks 23(2): 226-238 (2010) |
| 2009 |
| 17 |  | Hironori Fujisawa,
Youko Horiuchi,
Yoshiaki Harushima,
Toyoyuki Takada,
Shinto Eguchi,
Takako Mochizuki,
Takayuki Sakaguchi,
Toshihiko Shiroishi,
Nori Kurata:
SNEP: Simultaneous detection of nucleotide and expression polymorphisms using Affymetrix GeneChip.
BMC Bioinformatics 10: (2009) |
| 16 |  | Su-Yun Huang,
Yi-Ren Yeh,
Shinto Eguchi:
Robust Kernel Principal Component Analysis.
Neural Computation 21(11): 3179-3213 (2009) |
| 2008 |
| 15 |  | Md. Nurul Haque Mollah,
Shinto Eguchi:
Robust Composite Interval Mapping for QTL Analysis by Minimum beta-Divergence Method.
BIBM 2008: 115-120 |
| 14 |  | Masanori Kawakita,
Shinto Eguchi:
Boosting Method for Local Learning in Statistical Pattern Recognition.
Neural Computation 20(11): 2792-2838 (2008) |
| 13 |  | Takashi Takenouchi,
Shinto Eguchi,
Noboru Murata,
Takafumi Kanamori:
Robust Boosting Algorithm Against Mislabeling in Multiclass Problems.
Neural Computation 20(6): 1596-1630 (2008) |
| 2007 |
| 12 |  | Takafumi Kanamori,
Takashi Takenouchi,
Shinto Eguchi,
Noboru Murata:
Robust Loss Functions for Boosting.
Neural Computation 19(8): 2183-2244 (2007) |
| 11 |  | Md. Nurul Haque Mollah,
Shinto Eguchi,
Mihoko Minami:
Robust Prewhitening for ICA by Minimizing beta-Divergence and Its Application to FastICA.
Neural Processing Letters 25(2): 91-110 (2007) |
| 2006 |
| 10 |  | Tadayoshi Fushiki,
Hironori Fujisawa,
Shinto Eguchi:
Identification of biomarkers from mass spectrometry data using a "common" peak approach.
BMC Bioinformatics 7: 358 (2006) |
| 9 |  | Md. Nurul Haque Mollah,
Mihoko Minami,
Shinto Eguchi:
Exploring Latent Structure of Mixture ICA Models by the Minimum ß-Divergence Method.
Neural Computation 18(1): 166-190 (2006) |
| 2005 |
| 8 |  | Takashi Takenouchi,
Masaru Ushijima,
Shinto Eguchi:
GroupAdaBoost for Selecting Important Genes.
BIBE 2005: 218-221 |
| 7 |  | Ryuei Nishii,
Shinto Eguchi:
Supervised image classification by contextual AdaBoost based on posteriors in neighborhoods.
IEEE T. Geoscience and Remote Sensing 43(11): 2547-2554 (2005) |
| 2004 |
| 6 |  | Takafumi Kanamori,
Takashi Takenouchi,
Shinto Eguchi,
Noboru Murata:
The Most Robust Loss Function for Boosting.
ICONIP 2004: 496-501 |
| 5 |  | Isao Higuchi,
Shinto Eguchi:
Robust Principal Component Analysis with Adaptive Selection for Tuning Parameters.
Journal of Machine Learning Research 5: 453-471 (2004) |
| 4 |  | Takashi Takenouchi,
Shinto Eguchi:
Robustifying AdaBoost by Adding the Naive Error Rate.
Neural Computation 16(4): 767-787 (2004) |
| 3 |  | Noboru Murata,
Takashi Takenouchi,
Takafumi Kanamori,
Shinto Eguchi:
Information Geometry of U-Boost and Bregman Divergence.
Neural Computation 16(7): 1437-1481 (2004) |
| 2002 |
| 2 |  | Mihoko Minami,
Shinto Eguchi:
Robust Blind Source Separation by Beta Divergence.
Neural Computation 14(8): 1859-1886 (2002) |
| 1998 |
| 1 |  | Isao Higuchi,
Shinto Eguchi:
The Influence Function of Principal Component Analysis by Self-Organizing Rule.
Neural Computation 10(6): 1435-1444 (1998) |