Accelerated Gossip via Stochastic Heavy Ball Method

Abstract

In this paper we show how the stochastic heavy ball method (SHB)-a popular method for solving stochastic convex and non-convex optimization problems-operates as a randomized gossip algorithm. In particular, we focus on two special cases of SHB: the Randomized Kaczmarz method with momentum and its block variant. Building upon a recent framework for the design and analysis of randomized gossip algorithms [20] we interpret the distributed nature of the proposed methods. We present novel protocols for solving the average consensus problem where in each step all nodes of the network update their values but only a subset of them exchange their private values. Numerical experiments on popular wireless sensor networks showing the benefits of our protocols are also presented.