Paper avoids strict saddles in stochastic optimization without unit excitation assumption.
problem Avoiding strict saddles in stochastic optimization without unit excitation assumption.
method Pathwise Lyapunov-Perron framework, local smoothness, finite-moment assumptions.
result Avoidance of strict saddles for stochastic mirror descent and proximal-type methods.