1 citations · 1 across the 2 of their papers we have counts for
2 papers
stat.ML2023
How many Neurons do we need? A refined Analysis for Shallow Networks trained with Gradient Descent
Mike Nguyen, Nicole Mücke
We analyze the generalization properties of two-layer neural networks in the neural tangent kernel (NTK) regime, trained with gradient descent (GD). For early stopped GD we derive…
cs.LG2023★ 1 cited
Random feature approximation for general spectral methods
Mike Nguyen, Nicole Mücke
Random feature approximation is arguably one of the most popular techniques to speed up kernel methods in large scale algorithms and provides a theoretical approach to the analysis…