The content discusses the design and implementation of new privacy-preserving machine learning protocols for logistic regression and neural network models. It introduces the HawkSingle and HawkMulti protocols, focusing on efficient computation of activation functions and derivatives. The HawkMulti protocol allows for table reuse, reducing computational resources needed for training. Experimental evaluations show significant speed gains and accuracy improvements compared to existing methods.
Til et annet språk
fra kildeinnhold
arxiv.org
Viktige innsikter hentet fra
by Hamza Saleem... klokken arxiv.org 03-27-2024
https://arxiv.org/pdf/2403.17296.pdfDypere Spørsmål