3 papers
cs.LG2025
Relevance-driven Input Dropout: an Explanation-guided Regularization Technique
Shreyas Gururaj, Lars Grüne, Wojciech Samek +2
Overfitting is a well-known issue extending even to state-of-the-art (SOTA) Machine Learning (ML) models, resulting in reduced generalization, and a significant train-test performa…
math.OC2025
Performance guarantees for optimization-based state estimation using turnpike properties
Julian D. Schiller, Lars Grüne, and Matthias A. Müller
In this paper, we develop novel accuracy and performance guarantees for optimal state estimation of general nonlinear systems (in particular, moving horizon estimation, MHE). Our r…
math.OC2025
Stabilization of Strictly Pre-Dissipative Receding Horizon Linear Quadratic Control by Terminal Costs
Mario Zanon, Lars Grüne
Asymptotic stability in receding horizon control is obtained under a strict pre-dissipativity assumption, in the presence of suitable state constraints. In this paper we analyze ho…