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An Inexact Augmented Lagrangian Method for $(L_0, L_1)$-Smooth Convex Optimization
Augmented Lagrangian methods are among the most effective approaches for solving constrained convex optimization problems. However, classical complexity analyses of first-order methods applied within the augmented Lagrangian framework usually rely on the assumption that the objective function has a
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