Structure-aware methods for expensive derivative-free nonsmooth composite optimization
Author:
Publisher
Springer Science and Business Media LLC
Subject
Software,Theoretical Computer Science
Link
https://link.springer.com/content/pdf/10.1007/s12532-023-00245-5.pdf
Reference53 articles.
1. Audet, C., Hare, W.L.: Derivative-Free and Blackbox Optimization. Springer, Berlin (2017). https://doi.org/10.1007/978-3-319-68913-5
2. Audet, C., Hare, W.L.: Model-based methods in derivative-free nonsmooth optimization. In: A.M. Bagirov, M. Gaudioso, N. Karmitsa, M. Mäkelä (eds.) Numerical Nonsmooth Optimization, pp. 655–691. Springer, Berlin (2020). https://doi.org/10.1007/978-3-030-34910-3_19
3. Bagirov, A.M., Ganjehlou, A.N.: An approximate subgradient algorithm for unconstrained nonsmooth, nonconvex optimization. Math. Methods Oper. Res. 67(2), 187–206 (2008). https://doi.org/10.1007/s00186-007-0186-5
4. Bagirov, A.M., Jin, L., Karmitsa, N., Nuaimat, A.A., Sultanova, N.: Subgradient method for nonconvex nonsmooth optimization. J. Optim. Theory Appl. 157(2), 416–435 (2013). https://doi.org/10.1007/s10957-012-0167-6
5. Bagirov, A.M., Karasözen, B., Sezer, M.: Discrete gradient method: Derivative-free method for nonsmooth optimization. J. Optim. Theory Appl. 137(2), 317–334 (2007). https://doi.org/10.1007/s10957-007-9335-5
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