DP-KAN: Differentially Private Kolmogorov-Arnold Networks
Fuente:
arXiv
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866914875059470336 |
|---|---|
| author | Kalinin, Nikita P. Bombari, Simone Zakerinia, Hossein Lampert, Christoph H. |
| author_facet | Kalinin, Nikita P. Bombari, Simone Zakerinia, Hossein Lampert, Christoph H. |
| contents | We study the Kolmogorov-Arnold Network (KAN), recently proposed as an alternative to the classical Multilayer Perceptron (MLP), in the application for differentially private model training. Using the DP-SGD algorithm, we demonstrate that KAN can be made private in a straightforward manner and evaluated its performance across several datasets. Our results indicate that the accuracy of KAN is not only comparable with MLP but also experiences similar deterioration due to privacy constraints, making it suitable for differentially private model training. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_12569 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | DP-KAN: Differentially Private Kolmogorov-Arnold Networks Kalinin, Nikita P. Bombari, Simone Zakerinia, Hossein Lampert, Christoph H. Machine Learning Cryptography and Security We study the Kolmogorov-Arnold Network (KAN), recently proposed as an alternative to the classical Multilayer Perceptron (MLP), in the application for differentially private model training. Using the DP-SGD algorithm, we demonstrate that KAN can be made private in a straightforward manner and evaluated its performance across several datasets. Our results indicate that the accuracy of KAN is not only comparable with MLP but also experiences similar deterioration due to privacy constraints, making it suitable for differentially private model training. |
| title | DP-KAN: Differentially Private Kolmogorov-Arnold Networks |
| topic | Machine Learning Cryptography and Security |
| url | https://arxiv.org/abs/2407.12569 |