Makoto Aoshima - researchr alias

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Viewing Publication 1 - 9 from 9

2024

Asymptotic properties of hierarchical clustering in high-dimensional settingsKento Egashira, Kazuyoshi Yata, Makoto Aoshima. ma, 199:105251, 2024. [doi]

2022

Geometric classifiers for high-dimensional noisy dataAki Ishii, Kazuyoshi Yata, Makoto Aoshima. ma, 188:104850, 2022. [doi]

2021

Clustering by principal component analysis with Gaussian kernel in high-dimension, low-sample-size settingsYugo Nakayama, Kazuyoshi Yata, Makoto Aoshima. ma, 185:104779, 2021. [doi]

2016

High-dimensional inference on covariance structures via the extended cross-data-matrix methodologyKazuyoshi Yata, Makoto Aoshima. ma, 151:151-166, 2016. [doi]

2013

PCA consistency for the power spiked model in high-dimensional settingsKazuyoshi Yata, Makoto Aoshima. ma, 122:334-354, 2013. [doi]

Correlation tests for high-dimensional data using extended cross-data-matrix methodologyKazuyoshi Yata, Makoto Aoshima. ma, 117:313-331, 2013. [doi]

2012

Effective PCA for high-dimension, low-sample-size data with noise reduction via geometric representationsKazuyoshi Yata, Makoto Aoshima. ma, 105(1):193-215, 2012. [doi]

2010

Effective PCA for high-dimension, low-sample-size data with singular value decomposition of cross data matrixKazuyoshi Yata, Makoto Aoshima. ma, 101(9):2060-2077, 2010. [doi]

2009

Optimal discriminant functions for normal populationsHirofumi Wakaki, Makoto Aoshima. ma, 100(1):58-69, 2009. [doi]

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