Fast deflation sparse principal component analysis via subspace projections
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Publication:5107781
DOI10.1080/00949655.2020.1728761OpenAlexW3007811911MaRDI QIDQ5107781
Publication date: 28 April 2020
Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1912.01449
Cites Work
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- Finding structure with randomness: Probabilistic algorithms for constructing approximate matrix decompositions
- Simplicial principal component analysis for density functions in Bayes spaces
- Sparse principal component analysis and iterative thresholding
- Sparse principal component analysis via regularized low rank matrix approximation
- Sparse principal component regression for generalized linear models
- Sparse principal component regression with adaptive loading
- Principal component analysis.
- Coordinate descent algorithms
- Efficient algorithms for CUR and interpolative matrix decompositions
- Generalized power method for sparse principal component analysis
- New and Improved Johnson–Lindenstrauss Embeddings via the Restricted Isometry Property
- An Algorithm for the Principal Component Analysis of Large Data Sets
- Computation of Plain Unitary Rotations Transforming a General Matrix to Triangular Form
- Projection and deflation method for partial pole assignment in linear state feedback
- Principal component analysis-based muscle identification for myoelectric-controlled exoskeleton knee
- Principal-component-based generalized-least-squares approach for panel data
- Principal Component Analysis of High-Frequency Data
- Fast Monte Carlo Algorithms for Matrices II: Computing a Low-Rank Approximation to a Matrix
- Unitary Triangularization of a Nonsymmetric Matrix
- A Direct Formulation for Sparse PCA Using Semidefinite Programming