[thomasahle]

> As touched upon in the article, the objective not being differentiable is a big deal for modern machine learning methods.

I'm not sure the absolute value is a big problem here. You still get a convex optimization problem. In neural networks a lot of people use ReLU or step activations functions, which are no more differentiable than the absolute value.