SILAGE is a memory-efficient, full-gradient-free method for nonconvex optimization over nested double finite-sum problems, removing periodic full-gradient refreshes while using only O(n) memory and adapting to across- and within-group data heterogeneity.
Jun 14, 2026
Six practical algorithmic extensions of the EF21 error feedback method for communication-efficient distributed learning, with strong convergence guarantees.
Oct 7, 2021