## Branch-and-bound Algorithm for Optimal Sparse Canonical Correlation Analysis

Canonical correlation analysis (CCA) is a family of multivariate statistical methods for extracting mutual information contained in multiple datasets. To improve the interpretability of CCA, here we focus on the mixed-integer optimization (MIO) approach to sparse estimation. This approach was first proposed for sparse linear regression in the 1970s, but it has recently received renewed … Read more