# On the structure of regularization paths for piecewise differentiable regularization terms

B. Gebken, K. Bieker, S. Peitz, Journal of Global Optimization (2022).

Journal Article | English
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Abstract
Regularization is used in many different areas of optimization when solutions are sought which not only minimize a given function, but also possess a certain degree of regularity. Popular applications are image denoising, sparse regression and machine learning. Since the choice of the regularization parameter is crucial but often difficult, path-following methods are used to approximate the entire regularization path, i.e., the set of all possible solutions for all regularization parameters. Due to their nature, the development of these methods requires structural results about the regularization path. The goal of this article is to derive these results for the case of a smooth objective function which is penalized by a piecewise differentiable regularization term. We do this by treating regularization as a multiobjective optimization problem. Our results suggest that even in this general case, the regularization path is piecewise smooth. Moreover, our theory allows for a classification of the nonsmooth features that occur in between smooth parts. This is demonstrated in two applications, namely support-vector machines and exact penalty methods.
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Journal of Global Optimization
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### Cite this

Gebken B, Bieker K, Peitz S. On the structure of regularization paths for piecewise differentiable regularization terms. Journal of Global Optimization. Published online 2022. doi:10.1007/s10898-022-01223-2
Gebken, B., Bieker, K., & Peitz, S. (2022). On the structure of regularization paths for piecewise differentiable regularization terms. Journal of Global Optimization. https://doi.org/10.1007/s10898-022-01223-2
@article{Gebken_Bieker_Peitz_2022, title={On the structure of regularization paths for piecewise differentiable regularization terms}, DOI={10.1007/s10898-022-01223-2}, journal={Journal of Global Optimization}, author={Gebken, Bennet and Bieker, Katharina and Peitz, Sebastian}, year={2022} }
Gebken, Bennet, Katharina Bieker, and Sebastian Peitz. “On the Structure of Regularization Paths for Piecewise Differentiable Regularization Terms.” Journal of Global Optimization, 2022. https://doi.org/10.1007/s10898-022-01223-2.
B. Gebken, K. Bieker, and S. Peitz, “On the structure of regularization paths for piecewise differentiable regularization terms,” Journal of Global Optimization, 2022, doi: 10.1007/s10898-022-01223-2.
Gebken, Bennet, et al. “On the Structure of Regularization Paths for Piecewise Differentiable Regularization Terms.” Journal of Global Optimization, 2022, doi:10.1007/s10898-022-01223-2.
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