This paper presents an automatic procedure for the optimization of the hyperparameters of a delay rational model approximating the frequency-domain behavior of high-speed interconnects. The proposed model is built via a kernel-based regression, such as the Least-Square Support Vector Machine (LS-SVM), by considering an ad-hoc kernel with two hyperparameters related to the propagation delays introduced by the system. Such hyperparameters, along with the Tikhonov regularizer used by the LS-SVM regression, are carefully tuned via an automatic approach based on a k-fold cross-validation and Bayesian optimization. The feasibility of the effectiveness of the proposed modeling approach are investigated on a high-speed link.

Bayesian Optimization of Hyperparameters in Kernel-Based Delay Rational Models / Treviso, Felipe; Trinchero, Riccardo; Canavero, Flavio G.. - In: IEEE ELECTROMAGNETIC COMPATIBILITY MAGAZINE. - ISSN 2162-2264. - ELETTRONICO. - 10:2(2021), pp. 90-93. [10.1109/MEMC.2021.9477255]

Bayesian Optimization of Hyperparameters in Kernel-Based Delay Rational Models

Treviso, Felipe;Trinchero, Riccardo;Canavero, Flavio G.
2021

Abstract

This paper presents an automatic procedure for the optimization of the hyperparameters of a delay rational model approximating the frequency-domain behavior of high-speed interconnects. The proposed model is built via a kernel-based regression, such as the Least-Square Support Vector Machine (LS-SVM), by considering an ad-hoc kernel with two hyperparameters related to the propagation delays introduced by the system. Such hyperparameters, along with the Tikhonov regularizer used by the LS-SVM regression, are carefully tuned via an automatic approach based on a k-fold cross-validation and Bayesian optimization. The feasibility of the effectiveness of the proposed modeling approach are investigated on a high-speed link.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2911831