I was wondering about how someone would extend LSA techniques into tensor rank-k spaces where k > 2, so one could add as many datapoints/features collected othe

I was wondering about how someone would extend LSA techniques into tensor rank-k spaces where k > 2, so one could add as many datapoints/features collected other than terms and frequency of such (like parts of speech, sound clips, etc). I also want to use something like this for spacial filtering of eeg data. Ideally, i would use the Jacobi-Davidson Method[0], but armadillo only has n x m partial singular value decomposition. [0] http://netlib.org/utk/people/JackDongarra/etemplates/node340.html http://netlib.org/utk/people/JackDongarra/etemplates/node340...