Results 231 to 240 of about 50,718 (252)

Sparse Principal Component Analysis in Hilbert Space

Scandinavian Journal of Statistics, 2014
AbstractTechnical advances in many areas have produced more complicated high‐dimensional data sets than the usual high‐dimensional data matrix, such as the fMRI data collected in a period for independent trials, or expression levels of genes measured in different tissues.
Qi, Xin, Luo, Ruiyan
openaire   +2 more sources

Automatic sparse principal component analysis

Canadian Journal of Statistics, 2020
The wide availability of computers enables us to accumulate a huge amount of data, thus effective tools to extract information from the huge volume of data have become critical. Principal component analysis (PCA) is a useful and traditional tool for dimensionality reduction of massive high‐dimensional datasets. Recently, sparse principal component (PC)
Heewon Park, Rui Yamaguchi, Seiya Imoto, Satoru Miyano   +3 more
openaire   +2 more sources

An exact approach to sparse principal component analysis

Computational Statistics, 2009
In sparse principal components analysis (sPCA) one looks for principal directions \(\beta\) in the set of vectors with a limited number of nonzero entries. E.g., the first sPCA component of the covariance matrix \(Z\) is defined as the solution of the optimization problem \(\max_\beta \beta' Z\beta\) under the constraints \(\beta'\beta=1\) and ...
openaire   +2 more sources

Bayesian robust principal component analysis with structured sparse component

Computational Statistics & Data Analysis, 2017
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Ningning Han, Yumeng Song, Zhanjie Song
openaire   +1 more source

Exactly Uncorrelated Sparse Principal Component Analysis

Journal of Computational and Graphical Statistics, 2023
Oh-Ran Kwon, Zhaosong Lu, Hui Zou
openaire   +2 more sources

Eigenvectors From Eigenvalues Sparse Principal Component Analysis

Journal of Computational and Graphical Statistics, 2022
Hildreth Robert Frost
exaly  

Sparse Principal Component Analysis for Natural Language Processing

Annals of Data Science, 2023
Reza Drikvandi
exaly  

Sparse Multivariate Functional Principal Component Analysis

Stat, 2022
Jun Song, Kyongwon Kim
exaly  

Sparse Principal Component Analysis Using Bootstrap Method

Chemical Engineering Science, 2021
Salim Ahmed, Syed Imtiaz, Abdalhamid Rahoma   +2 more
exaly  

Sparse Principal Component Analysis for High-Dimensional Stationary Time Series

Scandinavian Journal of Statistics, 2023
Masanobu Taniguchi, Yan Liu, Yuichi Gotō   +2 more
exaly