2025
Convergence of the Gradient Flow for Shallow ReLU Networks on Weakly Interacting Data
NeurIPS 2025poster
We analyse the convergence of one-hidden-layer ReLU networks trained by gradient flow on $n$ data points. Our main contribution leverages the high dimensionality of the ambient space, which implies low correlation of the input samples, to demonstrate that a network with width of order $\log(n)$ neur…