17 citations · 67 across the 16 of their papers we have counts for
3 papers · 2 filters
Escaping mediocrity: how two-layer networks learn hard generalized linear models with SGD
Luca Arnaboldi, Florent Krzakala, Bruno Loureiro +1
This study explores the sample complexity for two-layer neural networks to learn a generalized linear target function under Stochastic Gradient Descent (SGD), focusing on the chall…
How Two-Layer Neural Networks Learn, One (Giant) Step at a Time
Yatin Dandi, Florent Krzakala, Bruno Loureiro +2
For high-dimensional Gaussian data, we investigate theoretically how the features of a two-layer neural network adapt to the structure of the target function through a few large ba…
From high-dimensional & mean-field dynamics to dimensionless ODEs: A unifying approach to SGD in two-layers networks
Luca Arnaboldi, Ludovic Stephan, Florent Krzakala +1
This manuscript investigates the one-pass stochastic gradient descent (SGD) dynamics of a two-layer neural network trained on Gaussian data and labels generated by a similar, thoug…