Before revision:  We present neural fixed-point acceleration , a framework to automatically learn to accelerate convex fixed-point problems that are drawn from a distribution , using ideas from meta-learning and classical acceleration algorithms .
After revision:  We present neural fixed-point acceleration which combines ideas from meta-learning and classical acceleration methods to automatically learn to accelerate convex fixed-point problems that are drawn from a distribution , using ideas from meta-learning and classical acceleration algorithms .