Neural Quadratic Forms: A Unified Minimal Model for Sudden Learning and Scaling Laws

Neural networks trained by gradient descent on a smooth cost function can nevertheless learn in steps: the cost holds on long plateaus and then drops abruptly. Meanwhile, training losses instead follow smooth power laws. Variants of both behaviors occur in architectures with very different microscop...