A Theory of Generalization in Deep Learning
arXiv:2605.01172v1 Announce Type: new
Abstract: We present a non-asymptotic theory of generalization in deep learning where the empirical neural tangent kernel partitions the output space. In directions corresponding to signal, error dissipates rapidl…