4 papers
Adaptive Kernel Ridge Regression with Linear Structure: Sharp Oracle Inequalities and Minimax Optimality
Xin Bing, Chao Wang
Kernel ridge regression (KRR) is a widely used nonparametric method due to its strong theoretical guarantees and computational convenience. However, standard KRR does not distingui…
Kernel Ridge Regression with Predicted Feature Inputs and Applications to Factor-Based Nonparametric Regression
Xin Bing, Xin He, Chao Wang
Kernel methods, particularly kernel ridge regression (KRR), are time-proven, powerful nonparametric regression techniques known for their rich capacity, analytical simplicity, and…
Towards a Unified Analysis of Kernel-based Methods Under Covariate Shift
Xingdong Feng, Xin He, Caixing Wang +2
Covariate shift occurs prevalently in practice, where the input distributions of the source and target data are substantially different. Despite its practical importance in various…
Transfer Learning for Kernel-based Regression
Chao Wang, Caixing Wang, Xin He +1
In recent years, transfer learning has garnered significant attention. Its ability to leverage knowledge from related studies to improve generalization performance in a target stud…