Alessandro Ingrosso

Neural networks trained with SGD learn distributions of increasing complexity

The uncanny ability of over-parameterised neural networks to generalise well has been explained using various "simplicity biases". These theories postulate that neural networks avoid overfitting by first fitting simple, linear classifiers before learning more complex, non-linear functions. Meanwhile…