SILAGE is a variance-reduced algorithm for nested finite-sum nonconvex optimization that uses O(n) memory, evaluates at most one local group gradient per iteration, and adapts convergence to data heterogeneity parameters δ1 and δ2.
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SILAGE: Memory-Efficient, Full-Gradient-Free Nonconvex Optimization for Nested Finite Sums
SILAGE is a variance-reduced algorithm for nested finite-sum nonconvex optimization that uses O(n) memory, evaluates at most one local group gradient per iteration, and adapts convergence to data heterogeneity parameters δ1 and δ2.