Reviews: DINGO: Distributed Newton-Type Method for Gradient-Norm Optimization

Neural Information Processing Systems 

In this paper, the authors propose a distributed Newton method for gradient-norm optimization. The method does not impose any specific form on the underlying objective function. The authors present convergence analysis for the method and illustrate the performance of the method on a convex problem (in the main paper). Originality: The topic of the paper, in my opinion, is very interesting. The paper presents an efficient Newton method that is motivated via the optimization of the norm of the gradient.