Variable selection using axis-aligned random projections for partial least-squares regression
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Publication:6547786
DOI10.1007/s11222-024-10417-5zbMATH Open1539.62026MaRDI QIDQ6547786
Kok Lay Teo, Pei Wang, Xin Zeng, Youwu Lin, Shuai Huang
Publication date: 31 May 2024
Published in: Statistics and Computing (Search for Journal in Brave)
Computational methods for problems pertaining to statistics (62-08) Estimation in multivariate analysis (62H12) Linear regression; mixed models (62J05)
Cites Work
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- Variable Selection Using a Smooth Information Criterion for Distributional Regression Models
- Extensions of Lipschitz maps into Banach spaces
- Partial least squares prediction in high-dimensional regression
- Envelope-based sparse partial least squares
- Variable selection using conditional AIC for linear mixed models with data-driven transformations
- A Sparse PLS for Variable Selection when Integrating Omics Data
- Computational Advertising: Techniques for Targeting Relevant Ads
- Randomized Algorithms for Matrices and Data
- Bayesian Wavelet Regression on Curves With Application to a Spectroscopic Calibration Problem
- Sparse Partial Least Squares Regression for Simultaneous Dimension Reduction and Variable Selection
- How to Reduce Dimension With PCA and Random Projections?
- Sparse Principal Component Analysis via Axis-Aligned Random Projections
- Targeted Random Projection for Prediction From High-Dimensional Features
- Random-projection Ensemble Classification
- Variable selection and regularization via arbitrary rectangle-range generalized elastic net
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