1. A. C. B. de Oliveira, R. Wang, I.R. Manchester, and E. D. Sontag. Remarks on Lipschitz-minimal interpolation: Generalization bounds and neural network implementation. In Proc. 65th IEEE Conference on Decision and Control (CDC), 2026. Note: Submitted. Also arXiv:2603.19524. Abstract:

   This notes estabilishes a theoretical framework for finding (potentially overparameterized) approximations of a function on a compact with \apriori guarantees for the generalization error of the resulting approximation. The results presented theoretically here are then applied for the scenario of a deep ReLU network.

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