Sparse canonical correlation analysis

05/30/2017
by   Xiaotong Suo, et al.
0

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.

READ FULL TEXT

Please sign up or login with your details

Forgot password? Click here to reset