3 citations · 13 across the 25 of their papers we have counts for
4 papers · 1 filter
Risk Equivalence between RKHS Regression and Sequence Models for Lipschitz Spectral Algorithms
Yicheng Li, Yuqian Cheng, Zhuo Chen +1
Kernel spectral algorithms are often summarized by convergence rates, which hide how their risk depends jointly on regularization, noise, the population spectrum, target coefficien…
Large Dimensional Kernel Ridge Regression: Extending to Product Kernels
Yang Zhou, Yicheng Li, Yuqian Cheng +1
Recent studies have reported and in large dimensional kernel ridge regression (KRR). However, these findings are…
Optimal Confidence Band for Kernel Gradient Flow Estimator
Yuqian Cheng, Zhuo Chen, Qian Lin
In this paper, we investigate the supremum-norm generalization error and the uniform inference for a specific class of kernel regression methods, namely the kernel gradient flows.…
Learning Curves and Benign Overfitting of Spectral Algorithms in Large Dimensions
Weihao Lu, Qian Lin, Yingcun Xia +1
Existing large-dimensional theory for spectral algorithms resolves either the optimally tuned point or the interpolation limit, but leaves the under-regularized regime unexplored.…