Proposes a Riemannian quasi-Newton bundle method with subgradient aggregation and limited-memory updates for nonsmooth optimization, proving global convergence to stationary points under a new semismoothness assumption.
IMA Jo urnal of Numerical Analysis 43(1), 293–325 (2023)
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A restricted memory quasi-Newton bundle method for nonsmooth optimization on Riemannian manifolds
Proposes a Riemannian quasi-Newton bundle method with subgradient aggregation and limited-memory updates for nonsmooth optimization, proving global convergence to stationary points under a new semismoothness assumption.