2 citations · 2 across the 2 of their papers we have counts for
2 papers
cs.LG2021★ 2 cited
Subquadratic Overparameterization for Shallow Neural Networks
Chaehwan Song, Ali Ramezani-Kebrya, Thomas Pethick +2
Overparameterization refers to the important phenomenon where the width of a neural network is chosen such that learning algorithms can provably attain zero loss in nonconvex train…
cs.LG2019
Nearly Minimal Over-Parametrization of Shallow Neural Networks
Armin Eftekhari, ChaeHwan Song, Volkan Cevher
A recent line of work has shown that an overparametrized neural network can perfectly fit the training data, an otherwise often intractable nonconvex optimization problem. For (ful…