This project aims to host multilinear subspace learning (MSL) algorithms for dimensionality reduction of multidimensional data through learning a low-dimensional subspace from tensorial representation directly.
The origin of MSL traces back to multi-way analysis in the 1960s and they have been studied extensively in face and gait recognition. With more connections revealed and analogies drawn between multilinear algorithms and their linear counterparts, MSL has become an exciting area...