3 citations · 10 across the 24 of their papers we have counts for
6 papers · 1 filter
On the Asymptotic Learning Curves of Kernel Ridge Regression under Power-law Decay
Yicheng Li, Haobo Zhang, Qian Lin
The widely observed 'benign overfitting phenomenon' in the neural network literature raises the challenge to the 'bias-variance trade-off' doctrine in the statistical learning theo…
Optimal Rate of Kernel Regression in Large Dimensions
Weihao Lu, Haobo Zhang, Yicheng Li +2
We perform a study on kernel regression for large-dimensional data (where the sample size is polynomially depending on the dimension of the samples, i.e., for…
On the Optimality of Misspecified Kernel Ridge Regression
Haobo Zhang, Yicheng Li, Weihao Lu +1
In the misspecified kernel ridge regression problem, researchers usually assume the underground true function , a less-smooth interpolation space of…
On the Eigenvalue Decay Rates of a Class of Neural-Network Related Kernel Functions Defined on General Domains
Yicheng Li, Zixiong Yu, Guhan Chen +1
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 . This…
Kernel interpolation generalizes poorly
Yicheng Li, Haobo Zhang, Qian Lin
One of the most interesting problems in the recent renaissance of the studies in kernel regression might be whether the kernel interpolation can generalize well, since it may help…
On the Optimality of Misspecified Spectral Algorithms
Haobo Zhang, Yicheng Li, Qian Lin
In the misspecified spectral algorithms problem, researchers usually assume the underground true function , a less-smooth interpolation space of a re…