It can be easily verified that W −0.25 , as computed over X, would recover back the original embeddings, that is, M (XW −0.25 ) = M (Z).
assuming that the embeddings X capture some second order similarity, it is possible to transform them so that they capture the corresponding first order similarity, and one can easily generalize this to higher order similarities by simply using smaller values of α.