Author

D. Hoang

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Preprint Aug 2026

A Data-dependent Early Stopping Rule using Rademacher Complexity with L1-norm

This work introduces an analytic framework that estimates the optimal time of early stopping without the need for training and can be successfully applied to nonlinear neural networks, as illustrated in the classification MNIST example.

D. Hoang, B. Berret, O. Bruneau et al. · 0 citations