3 papers
stat.ML2024
Optimal Kernel Quantile Learning with Random Features
Caixing Wang, Xingdong Feng
The random feature (RF) approach is a well-established and efficient tool for scalable kernel methods, but existing literature has primarily focused on kernel ridge regression with…
stat.ML2023
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…
stat.ML2023
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…