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.
Non- linearly preconditioned gradient methods under generalized smoothness.arXiv preprint arXiv:2502.08532, 2025
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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.