Yu-Xin Xia

On the convergence of doubly stochastic block gradient descent method for linear inverse problems

Stochastic gradient descent (SGD) and randomized block coordinate descent (RBCD) belong to two fundamentally different classes of stochastic iterative regularization methods, and are promising and popular for solving large-scale inverse problems, due to their excellent scalability with respect to data size and signal s...