Non-linear Canonical Correlation Analysis: A Compressed Representation Approach

31 Oct 2018Amichai PainskyMeir FederNaftali Tishby

Canonical Correlation Analysis (CCA) is a linear representation learning method that seeks maximally correlated variables in multi-view data. Non-linear CCA extends this notion to a broader family of transformations, which are more powerful in many real-world applications... (read more)

PDF Abstract

Results from the Paper


  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.