Tom McGrath says block-sparse methods need to learn subspace dimensionalities adaptively instead of fixing them in advance, since manually specifying the dimensions would require an impractical set of hyperparameters.

“in making it actually work and in not fixing the dimensionality as ahead of time because you know you don't want to have to put in some information like I think in this representation there are 7,000 two-dimensional features 400 three-dimensional features and five five-dimensional features like this is just a stupid set of hyperparameters to specify so you need to be able to adaptively learn the size of these subspaces and that's sort of the”

“Making this work at all and adaptively learning the size of these subspaces are kind of the key.”