I implemented Slope One for the netflix prize and found its results pretty unimpressive. So I decided to extend it to build a SVD predictor of Slope One values figuring it might do better than SVD by itself. It didn't.

Turns out increasing the dimensionality of the input 17 thousand times just reduces the amount training data for each attribute. Duh :)