Improved Convergence in Parameter-Agnostic Error Feedback through Momentum
We study normalized error feedback algorithms with momentum and parameter-agnostic stepsizes, eliminating the need for problem-dependent tuning while achieving competitive convergence rates.
Nov 1, 2025