姓 名：涂霁原
职 称：助理教授
研究方向：统计学习理论
教授课程：计算统计
E - mail：tujiyuan@mail.shufe.edu.cn
研究项目
序号 | 项目名称 | 项目编号 | 项目来源 | 起止时间 | 项目经费 |
研究领域:统计与优化的交叉领域，包括分布式学习、稳健学习、强化学习、贝叶斯学习等
教育经历:
2013.9-2017.6 上海交通大学，数学科学学院，数学与应用数学，学士
2017.9-2023.3 上海交通大学，数学科学学院，统计学，博士
工作经历
2023.3-2025.11 上海财经大学，数学学院，讲师
2025.11-至今上海财经大学，统计与数据科学学院，助理教授
研究成果
Tu, J., Liu, W., Mao, X., & Chen, X. (2021). Variance reduced median-of-means estimator for Byzantine-robust distributed inference. Journal of Machine Learning Research, 22(84), 1–67.
Tu, J., Liu, W., & Mao, X. (2023). Byzantine-robust distributed sparse learning for M-estimation. Machine Learning, 112, 3773–3804.
Tu, J., Liu, W., Mao, X., & Xu, M. (2024). Distributed semi-supervised sparse statistical inference. IEEE Transactions on Information Theory, 70(6), 4197–4217.
Tu, J., Liu, W., & Mao, X. (2024). Distributed estimation on semi-supervised generalized linear model. Journal of Machine Learning Research, 25(76), 1–41.
Liu, W., Tu, J., Mao, X., & Chen, X. (2024). Majority vote for distributed differentially private sign selection. The Annals of Statistics, 52(4), 1671–1690.
Liu, W., Tu, J., Chen, X., & Zhang, Y. (2025). Online estimation and inference for robust policy evaluation in reinforcement learning. The Annals of Statistics, 53(5), 2128–2152.
Liu, W., Mao, X., & Tu, J.* (2025). Communication-efficient distributed sparse learning with oracle property and geometric convergence. Journal of the American Statistical Association, to appear.
