Search Results for author:
Found 3 papers, 0 papers with code
Improve Generalization Ability of Deep Wide Residual Network with A Suitable Scaling Factor
Deep Residual Neural Networks (ResNets) have demonstrated remarkable success across a wide range of real-world applications.
Generalization Ability of Wide Residual Networks
This uniform convergence further guarantees that the generalization error of the residual network converges to that of the kernel regression with respect to the RNTK.
On the Eigenvalue Decay Rates of a Class of Neural-Network Related Kernel Functions Defined on General Domains
In this paper, we provide a strategy to determine the eigenvalue decay rate (EDR) of a large class of kernel functions defined on a general domain rather than $\mathbb S^{d}$.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
