1. A computer implemented method of structured latent factor analysis comprising: by a computer: learning latent factors of a set of data; modeling pairwise relationships among them and determining structural relationships through the use of a sparse Gaussian graphical model; and outputting an indication of the latent factor relationships; wherein said pairwise relationship modeling is performed according to the following pairwise Markov Random Field (MRF) prior on a vector of factors sε K : p ( s  μ , Θ ) = 1 Z ( μ , Θ ) exp ( - ∑ i = 1 K μ i s i - 1 2 ∑ i = 1 K ∑ j = 1 K θ ij s i s j ) ( 4 ) with parameter μ=[μ i ], symmetric Θ=[θ ij ], and partition function Z(μ, Θ) which normalizes the distribution.