这个项目是关于线性子空间学习（MSL）算法，学习低维子空间的张量数据直接从

This project aims to host multilinear subspace learning (MSL) algorithms. 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 to explore for applications involving large-scale multidimensional (tensorial) data as well as a challenging problem for machine learning researchers to tackle. MSL-based dimensionality reduction can be either tensor-to-tensor projection or tensor-to-vector projection.

MPCACodes
FERETC80A45.mat
GRResultsVerify.txt
GRTestMPCA.m
GRTestMPCALDA.m
MADAll.m
MPCA.m
MPCALDA.m
MPCApublications.bib
MPCA_TNN08_rev2012.pdf
ReadMe1.3.txt
SurveyMSL_PR2011.pdf
tensor_toolbox_2.1.zip
testData.m
USF17Gal.mat
USFGait17_32x22x10