In this technical report, we compare multiple reformulation techniques and solvers that can be used with the Julia package BilevelJuMP. We focus on the special case of Hyperparameter Tuning for Support Vector Regression. We describe a bilevel model for the problem in question. Then we present code for generating data and models that solve the problem. Finally, we present results and a brief analysis.
Cite
@article{arxiv.2305.17320,
title = {Comparing BilevelJuMP.jl Formulations: Support Vector Regression Hyperparameter Tuning},
author = {Joaquim Dias Garcia and Guilherme Bodin and Alexandre Street},
journal= {arXiv preprint arXiv:2305.17320},
year = {2023}
}
Comments
arXiv admin note: substantial text overlap with arXiv:2205.02307