16 citations · 69 across the 34 of their papers we have counts for
Showing cs.LGShow all
2 papers · 1 filter
cs.LG2022★ 2 cited
Learning ReLU networks to high uniform accuracy is intractable
Julius Berner, Philipp Grohs, Felix Voigtlaender
Statistical learning theory provides bounds on the necessary number of training samples needed to reach a prescribed accuracy in a learning problem formulated over a given target c…
cs.LG2021★ 6 cited
Proof of the Theory-to-Practice Gap in Deep Learning via Sampling Complexity bounds for Neural Network Approximation Spaces
Philipp Grohs, Felix Voigtlaender
We study the computational complexity of (deterministic or randomized) algorithms based on point samples for approximating or integrating functions that can be well approximated by…