lmbdaU = lmbda
allow model selection for constant rate
Option of F1/MMR for model selection
copy all params of soft impute
normalise lambdaV by m
Model selection on random params
typo
Constant rate fix for learning rate selection
Fixes to gradient/objective
Test scaling of gradients
Change objective to be tanh of rank loss per positive item
Another way to pick random ints
Test approx V derivative a bit better
Profile learning
Speed tweaks
reduce runs
Fix to use uniform sampling
fix for model selection
Model selection over learning rate
Derivative of V is a bit faster