@article{51208,
  abstract     = {{<jats:title>Abstract</jats:title><jats:p>Approximation of subdifferentials is one of the main tasks when computing descent directions for nonsmooth optimization problems. In this article, we propose a bisection method for weakly lower semismooth functions which is able to compute new subgradients that improve a given approximation in case a direction with insufficient descent was computed. Combined with a recently proposed deterministic gradient sampling approach, this yields a deterministic and provably convergent way to approximate subdifferentials for computing descent directions.</jats:p>}},
  author       = {{Gebken, Bennet}},
  issn         = {{0926-6003}},
  journal      = {{Computational Optimization and Applications}},
  keywords     = {{Applied Mathematics, Computational Mathematics, Control and Optimization}},
  publisher    = {{Springer Science and Business Media LLC}},
  title        = {{{A note on the convergence of deterministic gradient sampling in nonsmooth optimization}}},
  doi          = {{10.1007/s10589-024-00552-0}},
  year         = {{2024}},
}