to you know two of them as examples one is there's a very nice recent paper that that links the the ubiquitous to norm to norm of the weights penalty for learning to a particular measure of the second derivative of the prediction function all right so that it really does say that for at least a very very simple kind of network there's a link between the weight values of the weights and the wiggliness of s and then there's another school of approaches that looks at well we have a VQ tiling of the input space let's count the number of tiles because