The authors derive a clipped gradient tracking method with staggered variance reduction for RUC-regular finite-sum distributed optimization problems, establishing an O(∑ n_i^{1.5} + n_i^{0.5} ε^{-1}) complexity bound that relies only on local smoothness.
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Clipped Stochastic Gradient Tracking For Locally Smooth Functions
The authors derive a clipped gradient tracking method with staggered variance reduction for RUC-regular finite-sum distributed optimization problems, establishing an O(∑ n_i^{1.5} + n_i^{0.5} ε^{-1}) complexity bound that relies only on local smoothness.