Stochastic Gradient Descent for Stochastic Doubly-Nonconvex Composite Optimization

Understand

The stochastic gradient descent has been widely used for solving composite optimization problems in big data analyses.

• Many algorithms and convergence properties have been developed.
• The composite functions were convex primarily and gradually nonconvex composite functions have been adopted to obtain more desirable properties.
• The convergence properties have been investigated, but only when either of composite functions is nonconvex.