learning. This framework offers two relaxations to balance system performance and
algorithm efficiency. We propose a new algorithm that takes advantage of this framework to
solve non-convex non-smooth problems with convergence guarantees. We present an in-
depth analysis of two large scale machine learning problems ranging from $\ell_1 $-
regularized logistic regression on CPUs to reconstruction ICA on GPUs, using 636TB of real …