Implicit bias produces neural scaling laws in learning curves, from perceptrons to deep networks
arXiv:2505.13230v3 Announce Type: replace
Abstract: Scaling laws in deep learning — empirical power-law relationships linking model performance to resource growth — have emerged as simple yet striking regularities across architectures, datasets, and…