Abstract: This work considers a high-dimensional decentralized optimization problem where computing the full gradient is prohibitively expensive. This is a common issue in Partial Difference Equation ...

Abstract: This paper proposes two accelerated gradient descent algorithms for systems with missing input data with the aim at achieving fast convergence rates. Based on the inverse auxiliary model, ...