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math.OC2020
On the Saturation Phenomenon of Stochastic Gradient Descent for Linear Inverse Problems
Bangti Jin, Zehui Zhou, Jun Zou
Stochastic gradient descent (SGD) is a promising method for solving large-scale inverse problems, due to its excellent scalability with respect to data size. The current mathematic…
math.OC2019★ 5 cited
On the Convergence of Stochastic Gradient Descent for Nonlinear Ill-Posed Problems
Bangti Jin, Zehui Zhou, Jun Zou
In this work, we analyze the regularizing property of the stochastic gradient descent for the efficient numerical solution of a class of nonlinear ill-posed inverse problems in Hil…