Scaling Laws and Spectra of Shallow Neural Networks in the Feature Learning Regime

arXiv:2509.24882v3 Announce Type: replace-cross Abstract: Neural scaling laws underlie many of the recent advances in deep learning, yet their theoretical understanding remains largely confined to linear models. In this work, we present a systematic analysis of scaling laws for quadratic and diagonal neural networks in…

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Source: cs.AI updates on arXiv.org

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