1 citations · 1 across the 3 of their papers we have counts for
3 papers
stat.ML2026
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.…
cs.LG2025
Alignment-Sensitive Minimax Rates for Spectral Algorithms with Learned Kernels
Dongming Huang, Zhifan Li, Yicheng Li +1
We study spectral algorithms in the setting where kernels are learned from data. We introduce the effective span dimension (ESD), an alignment-sensitive complexity measure that dep…
math.ST2024★ 1 cited
The Optimality of Kernel Classifiers in Sobolev Space
Jianfa Lai, Zhifan Li, Dongming Huang +1
Kernel methods are widely used in machine learning, especially for classification problems. However, the theoretical analysis of kernel classification is still limited. This paper…