Regularization appropriate regularization parameter, we want to (a) satisfy biological plausibility conditions of fascicles as well as (b)

Finding an appropriate value for hyper-parameters is always a challenge in machine learning problems. We do not yet compare to prior tractography algorithms. The availability of a ground truth Phi let's us focus our investigation into the soundness With the additional space in the camera-ready, we can include more background and discussion on ENCODE. Our solution exploits the inherent sparseness in the optimization. However, this does not need to be run for each step of the optimization and is not expensive to do once upfront.