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[3]
2024 | Conference Paper | LibreCat-ID: 46649 | OA
Hotegni SS, Berkemeier MB, Peitz S. Multi-Objective Optimization for Sparse Deep Multi-Task Learning. In: 2024 International Joint Conference on Neural Networks (IJCNN). IEEE; 2024:9. doi:10.1109/IJCNN60899.2024.10650994
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[2]
2022 | Preprint | LibreCat-ID: 33150 | OA
Berkemeier MB, Peitz S. Multi-Objective Trust-Region Filter Method for Nonlinear Constraints using Inexact Gradients. arXiv:220812094. Published online 2022.
LibreCat | Download (ext.) | arXiv
 
[1]
2021 | Journal Article | LibreCat-ID: 21337 | OA
Berkemeier MB, Peitz S. Derivative-Free Multiobjective Trust Region Descent Method Using Radial  Basis Function Surrogate Models. Mathematical and Computational Applications. 2021;26(2). doi:10.3390/mca26020031
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3 Publications

Mark all

[3]
2024 | Conference Paper | LibreCat-ID: 46649 | OA
Hotegni SS, Berkemeier MB, Peitz S. Multi-Objective Optimization for Sparse Deep Multi-Task Learning. In: 2024 International Joint Conference on Neural Networks (IJCNN). IEEE; 2024:9. doi:10.1109/IJCNN60899.2024.10650994
LibreCat | DOI | Download (ext.)
 
[2]
2022 | Preprint | LibreCat-ID: 33150 | OA
Berkemeier MB, Peitz S. Multi-Objective Trust-Region Filter Method for Nonlinear Constraints using Inexact Gradients. arXiv:220812094. Published online 2022.
LibreCat | Download (ext.) | arXiv
 
[1]
2021 | Journal Article | LibreCat-ID: 21337 | OA
Berkemeier MB, Peitz S. Derivative-Free Multiobjective Trust Region Descent Method Using Radial  Basis Function Surrogate Models. Mathematical and Computational Applications. 2021;26(2). doi:10.3390/mca26020031
LibreCat | DOI | Download (ext.)
 

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Citation Style: AMA

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