A proximal limited-memory quasi-Newton scheme is developed for nonsmooth nonconvex optimization, with global convergence proven under mild assumptions and rates under the Kurdyka-Lojasiewicz property.
Accelerating the DC al- gorithm for smooth functions
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A nonmonotone subgradient algorithm is developed for upper-C^2 optimization on submanifolds with stationarity and KL-based convergence guarantees.
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Proximal Limited-Memory Quasi-Newton Methods for Nonsmooth Nonconvex Optimization
A proximal limited-memory quasi-Newton scheme is developed for nonsmooth nonconvex optimization, with global convergence proven under mild assumptions and rates under the Kurdyka-Lojasiewicz property.
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A Nonmonotone Descent Method for Optimization Problems Defined by Upper-$\mathcal{C}^2 $ Functions over Submanifolds
A nonmonotone subgradient algorithm is developed for upper-C^2 optimization on submanifolds with stationarity and KL-based convergence guarantees.