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ORCIDWenwu Wang 0002
Person information
- affiliation: Qufu Normal University, Qufu, Shandong, China
Other persons with the same name
- Wenwu Wang 0001
![[0000-0002-8393-5703]](https://dblp.uni-trier.de./img/orcid-mark.12x12.png "0000-0002-8393-5703")
— University of Surrey, Guildford, UK - Wenwu Wang 0003 — Xidian University, Xi'an, China
- Wenwu Wang 0004 — Wuhan University, Wuhan, China
- Wenwu Wang 0005 — Harbin Institute of Technology, Harbin, China
- Wenwu Wang 0006 — Chinese Academy of Sciences, Institute of Microelectronics, Beijing, China
- Wenwu Wang 0007 — Sichuan University, School of Mechanical Engineering, Chengdu, China
- Wenwu Wang 0008 — Wuhan University of Science and Technology, School of Information Science and Engineering, China
- Wenwu Wang 0009 — Chinese Academy of Sciences, Institute of Microelectronics, Beijing, China
- Wenwu Wang 0010 — Guangxi University of Science and Technology, China
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2020 – today
- 2024
[j7]Deru Kong, Shengli Zhao, Wenwu Wang:
Nonparametric derivative estimation with bimodal kernels under correlated errors. Comput. Stat. 39(4): 1847-1865 (2024)- 2022
- [j6]Wenwu Wang, Jun Lu, Tiejun Tong, Zhonghua Liu:
Debiased learning and forecasting of first derivative. Knowl. Based Syst. 236: 107781 (2022) - 2021
- [j5]Jun Lu, Lu Lin, Wenwu Wang:
Partition-based feature screening for categorical data via RKHS embeddings. Comput. Stat. Data Anal. 157: 107176 (2021)
2010 – 2019
- 2019
- [j4]Wenwu Wang, Ping Yu, Lu Lin, Tiejun Tong:
Robust Estimation of Derivatives Using Locally Weighted Least Absolute Deviation Regression. J. Mach. Learn. Res. 20: 60:1-60:49 (2019) - 2017
- [j3]Wenwu Wang, Ping Yu:
Asymptotically optimal differenced estimators of error variance in nonparametric regression. Comput. Stat. Data Anal. 105: 125-143 (2017) - [j2]Wenwu Wang, Lu Lin, Li Yu:
Optimal variance estimation based on lagged second-order difference in nonparametric regression. Comput. Stat. 32(3): 1047-1063 (2017) - 2015
- [j1]Wenwu Wang, Lu Lin:
Derivative estimation based on difference sequence via locally weighted least squares regression. J. Mach. Learn. Res. 16: 2617-2641 (2015)
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