Sparse canonical correlation analysis algorithm with alternating direction method of multipliers
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Publication:5088121
DOI10.1080/03610918.2018.1520867OpenAlexW2911528233WikidataQ128549934 ScholiaQ128549934MaRDI QIDQ5088121
Publication date: 4 July 2022
Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/03610918.2018.1520867
multivariate data analysisalternating direction method of multipliers (ADMM)sparse canonical correlation analysis (SCCA)\(\ell 1\)-norm optimization
Uses Software
Cites Work
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- A penalized matrix decomposition, with applications to sparse principal components and canonical correlation analysis
- Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
- Sparse canonical correlation analysis
- Color image canonical correlation analysis for face feature extraction and recognition
- On the Douglas-Rachford splitting method and the proximal point algorithm for maximal monotone operators
- Sparse CCA using a lasso with positivity constraints
- Quantifying the Association between Gene Expressions and DNA-Markers by Penalized Canonical Correlation Analysis
- Sparse Canonical Correlation Analysis with Application to Genomic Data Integration
- The Split Bregman Method for L1-Regularized Problems
- Multi-Agent Distributed Optimization via Inexact Consensus ADMM
- Regularization and Variable Selection Via the Elastic Net
- Fast Image Recovery Using Variable Splitting and Constrained Optimization
- RELATIONS BETWEEN TWO SETS OF VARIATES
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