Towards a Unified Analysis of Kernel-based Methods Under Covariate Shift. - Xingdong Feng; Xin He; Caixing Wang; Chao Wang; Jingnan Zhang (NeurIPS, 2023)

Minimax Optimal Transfer Learning for Kernel-based Nonparametric Regression. - Chao Wang; Caixing Wang; Xin He; Xingdong Feng (CoRR, 2023)

Towards Theoretical Understanding of Learning Large-scale Dependent Data via Random Features. - Chao Wang; Xin Bing; Xin He; Caixing Wang (ICML, 2024)

Optimal Kernel Quantile Learning with Random Features. - Caixing Wang; Xingdong Feng (ICML, 2024)

Distributed High-Dimensional Quantile Regression: Estimation Efficiency and Support Recovery. - Caixing Wang; Ziliang Shen (ICML, 2024)

Communication-Efficient Nonparametric Quantile Regression via Random Features. - Caixing Wang; Tao Li; Xinyi Zhang; Xingdong Feng; Xin He (J. Comput. Graph. Stat., 2024)

Inertial Quadratic Majorization Minimization with Application to Kernel Regularized Learning. - Qiang Heng; Caixing Wang (CoRR, 2025)