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2020 – today
- 2024
[j17]Baohuai Sheng
:
Reproducing property of bounded linear operators and kernel regularized least square regressions. Int. J. Wavelets Multiresolution Inf. Process. 22(5): 2450013:1-2450013:42 (2024)- [j16]Xiaojun Sun, Baohuai Sheng, Lin Liu, Xiaoling Pan:
On the density of translation networks defined on the unit ball. Math. Found. Comput. 7(3): 386-404 (2024) - 2023
- [j15]Shuhua Wang, Baohuai Sheng:
Error analysis of kernel regularized pairwise learning with a strongly convex loss. Math. Found. Comput. 6(4): 625-650 (2023) - 2022
- [j14]Mingdang Tian, Baohuai Sheng, Shuhua Wang:
Some Upper Bounds for RKHS Approximation by Bessel Functions. Axioms 11(5): 233 (2022) - [j13]Baohuai Sheng, Dapao Zhou, Shuhua Wang:
The kernel regularized learning algorithm for solving Laplace equation with Dirichlet boundary. Int. J. Wavelets Multiresolution Inf. Process. 20(6): 2250031:1-2250031:27 (2022) - 2021
- [j12]Baohuai Sheng, Lan Zuo:
Error analysis of the kernel regularized regression based on refined convex losses and RKBSs. Int. J. Wavelets Multiresolution Inf. Process. 19(5): 2150012:1-2150012:52 (2021)
2010 – 2019
- 2019
- [j11]Shuhua Wang, Zhenlong Chen, Baohuai Sheng:
Convergence rate of SVM for kernel-based robust regression. Int. J. Wavelets Multiresolution Inf. Process. 17(1): 1950004:1-1950004:21 (2019) - 2018
- [j10]Baohuai Sheng, Hancan Zhu:
The convergence rate of semi-supervised regression with quadratic loss. Appl. Math. Comput. 321: 11-24 (2018) - 2017
- [j9]Baohuai Sheng, Daohong Xiang:
The performance of semi-supervised Laplacian regularized regression with the least square loss. Int. J. Wavelets Multiresolution Inf. Process. 15(2): 1750016:1-1750016:31 (2017) - [j8]Huanxiang Liu, Baohuai Sheng, Peixin Ye:
The improved learning rate for regularized regression with RKBSs. Int. J. Mach. Learn. Cybern. 8(4): 1235-1245 (2017) - 2015
- [j7]Baohuai Sheng, Daohong Xiang, Peixin Ye:
Convergence rate of semi-supervised gradient learning algorithms. Int. J. Wavelets Multiresolution Inf. Process. 13(4): 1550021:1-1550021:26 (2015) - 2014
- [j6]Baohuai Sheng, Liqin Duan, Pei-Xin Ye:
Strong Convex Loss Can Increase the Learning Rates of Online Learning. J. Comput. 9(7): 1606-1611 (2014) - 2012
- [j5]Pei-Xin Ye, Baohuai Sheng, Xiuhua Yuan:
Optimal order of truncation and aliasing errors for multi-dimensional Whittaker-Shannon sampling expansion. Int. J. Wirel. Mob. Comput. 5(4): 327-333 (2012) - [j4]Baohuai Sheng, Pei-Xin Ye:
Learning Rates of Support Vector Machine Classifiers with Data Dependent Hypothesis Spaces. J. Comput. 7(1): 252-257 (2012) - 2011
- [j3]Baohuai Sheng, Pei-Xin Ye:
Least Square Regression Learning with Data Dependent Hypothesis and Coefficient Regularzation. J. Comput. 6(4): 671-675 (2011)
2000 – 2009
- 2009
- [c1]Fengwei Li, Qingfang Ye, Baohuai Sheng:
On Integrity of Harary Graphs. COCOA 2009: 269-278 - 2008
- [j2]Baohuai Sheng, Jianli Wang, Ping Li:
The covering number for some Mercer kernel Hilbert spaces. J. Complex. 24(2): 241-258 (2008) - 2007
- [j1]Baohuai Sheng:
On Approximation By Reproducing Kernel Spaces in Weighted Lp Spaces. J. Syst. Sci. Complex. 20(4): 623-638 (2007)
Coauthor Index
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