A nonmonotone subgradient algorithm is developed for upper-C^2 optimization on submanifolds with stationarity and KL-based convergence guarantees.
On the convergence of the proximal algorithm for nons- mooth functions involving analytic features
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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.