Abstract: Nonconvex finite-sum optimization finds wide applications in various signal processing and machine learning tasks. The well-known stochastic gradient algorithms generate unbiased stochastic ...

Abstract: In this paper, we address the challenges of asynchronous gradient descent in distributed learning environments, particularly focusing on addressing the challenges of stale gradients and the ...