Comparative Evaluation of Nonlinear Regression Algorithms for Pre-Silicon Verification Methods
Alecsandra Rusu, Emilian David, Marina Ţopa, Bianca Cărbunescu, Andi Buzo, Georg Pelz · 2025
This paper presents a comparative evaluation of the performance and training time of ten nonlinear regression algorithms. The primary objective of this analysis was to identify the optimal trade-off between regression accuracy and training speed. Ultimately, the research aim is to enhance adaptive methods based on machine-learning algorithms, which are employed to improve the pre-silicon verification process of integrated circuits.