Stochastic Reformulations of Linear Systems: Algorithms and Convergence Theory
Stochastic Reformulations of Linear Systems: Algorithms and Convergence Theory
We develop a family of reformulations of an arbitrary consistent linear system into a stochastic problem. The reformulations are governed by two user-defined parameters: a positive definite matrix defining a norm, and an arbitrary discrete or continuous distribution over random matrices. Our reformulation has several equivalent interpretations, allowing for researchers …