AAMD combines preconditioning, acceleration, and adaptivity in mirror descent using a Lyapunov budget to achieve O(1/k^2) rates under dual relative smoothness and bounded sublevel sets.
Accelerated bregman proximal gradient methods for relatively smooth convex optimization.Computational Optimization and Applications, 79 (2):405–440, 2021
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Adaptive Accelerated Mirror Descent in Primal and Dual Spaces
AAMD combines preconditioning, acceleration, and adaptivity in mirror descent using a Lyapunov budget to achieve O(1/k^2) rates under dual relative smoothness and bounded sublevel sets.