Authors' Reply to the Comments by Kamata et al.

We thank Kamata et al. (2023) [1] for their interest in our work [2], and for providing an explanation of the quasi-linear kernel from a viewpoint of multiple kernel learning. In this letter, we first give a summary of the quasi-linear SVM. Then we provide a discussion on the novelty of quasi-linear kernels against multiple kernel learning. Finally, we explain the contributions of our work [2].

Automated summary

This letter acknowledges the interest of Kamata et al. in the work and their explanation of the quasi-linear kernel in the context of multiple kernel learning. The letter provides a summary of the quasi-linear SVM, discusses the novelty of quasi-linear kernels against multiple kernel learning, and explains the contributions of the authors' work.