Fast Kernel-Based Regularized System Identification using Bayesian Optimization

This paper proposes a scalable, matrix-free approach to kernel-based regularization for finite impulse response estimation. Our methodology is based on Bayesian optimization, a gradient-free global optimization strategy that can handle noisy objective function evaluations and is suitable for indirec... View More