On the benefit of overparameterisation in state reconstruction: An empirical study of the nonlinear case
On the benefit of overparameterisation in state reconstruction: An empirical study of the nonlinear case
The empirical success of machine learning models with many more parameters than measurements has generated an interest in the theory of overparameterisation, i.e., underdetermined models. This paradigm has recently been studied in domains such as deep learning, where one is interested in good (local) minima of complex, nonlinear loss functions. …