SGD convergence rates can be transferred: one Lyapunov calculation on a diffusion, then carried back window by window
Finite-time convergence bounds for stochastic gradient algorithms can be transferred from Lyapunov estimates for an associated stochastic differential equation, recovering known rates for strongly convex SGD and stochastic Heavy Ball.