Compared to their work, our usage of CP-decomposition is different in the application to feature learning: (1) We focus on dimensionality reduction of existing, well-verified features, while  generates new features (usually different from ours) by combining some "atom" features.
their work may ignore some useful features; it relies on binary features as supplementary but our model needs not.