Caixing Wang

According to our database, Caixing Wang authored at least 9 papers between 2023 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

High-Dimensional Differentially Private Quantile Regression: Distributed Estimation and Statistical Inference.

Ziliang Shen, Caixing Wang, Shaoli Wang, Yibo Yan

CoRR, August, 2025

Inertial Quadratic Majorization Minimization with Application to Kernel Regularized Learning.

Qiang Heng, Caixing Wang

CoRR, July, 2025

2024

Deep Nonparametric Quantile Regression under Covariate Shift.

Xingdong Feng, Xin He, Yuling Jiao, Lican Kang, Caixing Wang

J. Mach. Learn. Res., 2024

Communication-Efficient Nonparametric Quantile Regression via Random Features.

Caixing Wang, Tao Li, Xinyi Zhang, Xingdong Feng, Xin He

J. Comput. Graph. Stat., 2024

Distributed High-Dimensional Quantile Regression: Estimation Efficiency and Support Recovery.

Caixing Wang, Ziliang Shen

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Optimal Kernel Quantile Learning with Random Features.

Caixing Wang, Xingdong Feng

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Towards Theoretical Understanding of Learning Large-scale Dependent Data via Random Features.

Chao Wang, Xin Bing, Xin He, Caixing Wang

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Minimax Optimal Transfer Learning for Kernel-based Nonparametric Regression.

Chao Wang, Caixing Wang, Xin He, Xingdong Feng

CoRR, 2023

Towards a Unified Analysis of Kernel-based Methods Under Covariate Shift.

Xingdong Feng, Xin He, Caixing Wang, Chao Wang, Jingnan Zhang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023