B. Gebken, “A note on the convergence of deterministic gradient sampling in nonsmooth optimization,”10.1007/s10589-024-00552-0__Computational Optimization and Applications, 2024, doi:10.1007/s10589-024-00552-0 .
LibreCat: /record/51208
DOI: 10.1007/s10589-024-00552-0

K. Sonntag, B. Gebken, G. Müller, S. Peitz, and S. Volkwein, “A Descent Method for Nonsmooth Multiobjective Optimization in Hilbert Spaces,” arXiv:2402.06376. 2024.
LibreCat: /record/51334
arXiv: 	2402.06376

B. Gebken, K. Bieker, and S. Peitz, “On the structure of regularization paths for piecewise differentiable regularization terms,”10.1007/s10898-022-01223-2__Journal of Global Optimization, vol. 85, no. 3, pp. 709–741, 2023, doi:10.1007/s10898-022-01223-2 .
LibreCat: /record/27426
DOI: 10.1007/s10898-022-01223-2

M. Bernreuther et al., “Multiobjective Optimization of Non-Smooth PDE-Constrained Problems,” arXiv:2308.01113. 2023.
LibreCat: /record/46578
arXiv: 2308.01113

S. Banholzer, B. Gebken, M. Dellnitz, S. Peitz, and S. Volkwein, “ROM-Based Multiobjective Optimization of Elliptic PDEs via Numerical Continuation,” in Non-Smooth and Complementarity-Based Distributed Parameter Systems, H. Michael, H. Roland, K. Christian, U. Michael, and U. Stefan, Eds. Cham: Springer, 2022, pp. 43–76.
LibreCat: /record/16296
DOI: 10.1007/978-3-030-79393-7_3

B. Gebken, “Using second-order information in gradient sampling methods for  nonsmooth optimization,” arXiv:2210.04579. 2022.
LibreCat: /record/34618
arXiv: 2210.04579

B. Gebken, Computation and analysis of Pareto critical sets in smooth and nonsmooth multiobjective optimization. 2022.
LibreCat: /record/31556
DOI: 10.17619/UNIPB/1-1327

K. Bieker, B. Gebken, and S. Peitz, “On the Treatment of Optimization Problems with L1 Penalty Terms via Multiobjective Continuation,”10.1109/TPAMI.2021.3114962__IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 44, no. 11, pp. 7797–7808, 2022, doi:10.1109/TPAMI.2021.3114962 .
LibreCat: /record/20731
DOI: 10.1109/TPAMI.2021.3114962

B. Gebken and S. Peitz, “An efficient descent method for locally Lipschitz multiobjective optimization problems,” Journal of Optimization Theory and Applications, vol. 188, pp. 696–723, 2021.
LibreCat: /record/16867
DOI: 10.1007/s10957-020-01803-w

B. Gebken and S. Peitz, “Inverse multiobjective optimization: Inferring decision criteria from data,” Journal of Global Optimization, vol. 80, pp. 3–29, 2021.
LibreCat: /record/16295
DOI: 10.1007/s10898-020-00983-z

M. Dellnitz, B. Gebken, R. Gerlach, and S. Klus, “On the equivariance properties of self-adjoint matrices,”10.1080/14689367.2019.1661355__Dynamical Systems, vol. 35, no. 2, pp. 197–215, 2020, doi:10.1080/14689367.2019.1661355 .
LibreCat: /record/16712
DOI: 10.1080/14689367.2019.1661355

B. Gebken, S. Peitz, and M. Dellnitz, “On the hierarchical structure of Pareto critical sets,” Journal of Global Optimization, vol. 73, no. 4, pp. 891–913, 2019.
LibreCat: /record/10595
DOI: 10.1007/s10898-019-00737-6

B. Gebken, S. Peitz, and M. Dellnitz, “A Descent Method for Equality and Inequality Constrained Multiobjective Optimization Problems,” in Numerical and Evolutionary Optimization – NEO 2017, 2018.
LibreCat: /record/8750
DOI: 10.1007/978-3-319-96104-0_2