A new problem-parameter-free algorithm with nonmonotone line search and extrapolation achieves convergence for composite optimization beyond global Lipschitz gradient continuity under the Kurdyka-Łojasiewicz property without requiring bounded iterates.
Rockafellar.Convex Analysis
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Proposes ripALM, a relative inexact proximal ALM using one tolerance parameter, with new convergence analysis showing global and asymptotic linear rates without correction steps.
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A nonmonotone extrapolated proximal gradient-subgradient algorithm beyond global Lipschitz gradient continuity
A new problem-parameter-free algorithm with nonmonotone line search and extrapolation achieves convergence for composite optimization beyond global Lipschitz gradient continuity under the Kurdyka-Łojasiewicz property without requiring bounded iterates.
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ripALM: A Relative-Type Inexact Proximal Augmented Lagrangian Method for Linearly Constrained Convex Optimization
Proposes ripALM, a relative inexact proximal ALM using one tolerance parameter, with new convergence analysis showing global and asymptotic linear rates without correction steps.