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arXiv · 1705.10865

Sparse canonical correlation analysis

Xiaotong Suo·Victor Minden·Bradley Nelson·Robert Tibshirani·Michael Saunders
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Abstract

Canonical correlation analysis was proposed by Hotelling [6] and it measures linear relationship between two multidimensional variables. In high dimensional setting, the classical canonical correlation analysis breaks down. We propose a sparse canonical correlation analysis by adding l1 constraints on the canonical vectors and show how to solve it efficiently using linearized alternating direction method of multipliers (ADMM) and using TFOCS as a black box. We illustrate this idea on simulated data.

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Xiaotong Suo, Victor Minden, Bradley Nelson, Robert Tibshirani, Michael Saunders. 2017-06-02. Sparse canonical correlation analysis. https://arxiv.org/abs/1705.10865

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