The Double-Barrelled LASSO (Sparse Canonical Correlation Analysis)
published: Dec. 20, 2008, recorded: December 2008, views: 4803
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We present a new method which solves a double-barelled LASSO in a convex least squares approach. In the presented method we focus on the scenario where one is interested in (or limited to) a primal (feature) representation for the first view while having a dual (kernel) representation for the second view. DB-LASSO minimises the number of features used in both the primal and dual projections while minimising the error (maximising the correlation) between the two views.
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