139 citations · 170 across the 18 of their papers we have counts for
Showing stat.MLShow all
3 papers · 1 filter
stat.ML2023
The Learnability of Reproducing Kernel Hilbert Spaces
Hongrui Chen, Jihao Long, Lei Wu
In this work, we analyze the learnability of reproducing kernel Hilbert spaces (RKHS) under the norm, which is critical for understanding the performance of kernel metho…
stat.ML2023
A duality framework for analyzing random feature and two-layer neural networks
Hongrui Chen, Jihao Long, Lei Wu
We consider the problem of learning functions within the and Barron spaces, which play crucial roles in understanding random feature models (RFMs), two-layer ne…
stat.ML2021★ 1 cited
A spectral-based analysis of the separation between two-layer neural networks and linear methods
Lei Wu, Jihao Long
We propose a spectral-based approach to analyze how two-layer neural networks separate from linear methods in terms of approximating high-dimensional functions. We show that quanti…