Stochastic Push-Pull for Decentralized Nonconvex Optimization

To understand the convergence behavior of the Push–Pull method for decentralized optimization with stochastic gradients (Stochastic Push–Pull), this paper presents a comprehensive analysis. Specifically, we first clarify the algorithm’s underlying assumptions, particularly those regarding the network structure and weight matrices. Then, to establish the convergence rate under smooth nonconvex objectives, we introduce a general analytical framework that not only encompasses a broad class of decen