Caixing Wang

12 papers A* 4Journal 8
YearRankTypeTitle / Venue / Authors
2025 J jnl
High-Dimensional Differentially Private Quantile Regression: Distributed Estimation and Statistical Inference.
CoRR
Ziliang Shen, Caixing Wang, Shaoli Wang, Yibo Yan
2025 J jnl
Inertial Quadratic Majorization Minimization with Application to Kernel Regularized Learning.
CoRR
Qiang Heng, Caixing Wang
2024 J jnl
Communication-Efficient Nonparametric Quantile Regression via Random Features.
J. Comput. Graph. Stat.
Caixing Wang, Tao Li, Xinyi Zhang, Xingdong Feng, Xin He
2024 J jnl
Deep Nonparametric Quantile Regression under Covariate Shift.
J. Mach. Learn. Res.
Xingdong Feng, Xin He, Yuling Jiao, Lican Kang, Caixing Wang
2024 A* conf
Distributed High-Dimensional Quantile Regression: Estimation Efficiency and Support Recovery.
ICML
Caixing Wang, Ziliang Shen
2024 J jnl
Distributed High-Dimensional Quantile Regression: Estimation Efficiency and Support Recovery.
CoRR
Caixing Wang, Ziliang Shen
2024 A* conf
Optimal Kernel Quantile Learning with Random Features.
ICML
Caixing Wang, Xingdong Feng
2024 J jnl
Optimal Kernel Quantile Learning with Random Features.
CoRR
Caixing Wang, Xingdong Feng
2024 A* conf
Towards Theoretical Understanding of Learning Large-scale Dependent Data via Random Features.
ICML
Chao Wang, Xin Bing, Xin He, Caixing Wang
2023 J jnl
Minimax Optimal Transfer Learning for Kernel-based Nonparametric Regression.
CoRR
Chao Wang, Caixing Wang, Xin He, Xingdong Feng
2023 A* conf
Towards a Unified Analysis of Kernel-based Methods Under Covariate Shift.
NeurIPS
Xingdong Feng, Xin He, Caixing Wang, Chao Wang, Jingnan Zhang
2023 J jnl
Towards a Unified Analysis of Kernel-based Methods Under Covariate Shift.
CoRR
Xingdong Feng, Xin He, Caixing Wang, Chao Wang, Jingnan Zhang