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02/22/2023
On the efficiency-loss free ordering-robustness of product-PCA
This article studies the robustness of the eigenvalue ordering, an impor...
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06/08/2022
Robust self-tuning semiparametric PCA for contaminated elliptical distribution
Principal component analysis (PCA) is one of the most popular dimension ...
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04/29/2020
A generalized information criterion for high-dimensional PCA rank selection
Principal component analysis (PCA) is the most commonly used statistical...
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04/09/2020
TensorProjection Layer: A Tensor-Based Dimensionality Reduction Method in CNN
In this paper, we propose a dimensionality reduction method applied to t...
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01/31/2020
A Consistency Theorem for Randomized Singular Value Decomposition
The singular value decomposition (SVD) and the principal component analy...
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11/22/2019
2SDR: Applying Kronecker Envelope PCA to denoise Cryo-EM Images
Principal component analysis (PCA) is arguably the most widely used dime...
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12/30/2017
An ISIS screening approach involving threshold/partition for variable selection in linear regression
In linear regression, one can select a predictor if the absolute sample ...
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03/12/2015
