On Approximation By Reproducing Kernel Spaces in Weighted Lp Spaces. - Baohuai Sheng (J. Syst. Sci. Complex., 2007)

The covering number for some Mercer kernel Hilbert spaces. - Baohuai Sheng; Jianli Wang; Ping Li (J. Complex., 2008)

On Integrity of Harary Graphs. - Fengwei Li; Qingfang Ye; Baohuai Sheng (COCOA, 2009)

Least Square Regression Learning with Data Dependent Hypothesis and Coefficient Regularzation. - Baohuai Sheng; Pei-Xin Ye (J. Comput., 2011)

Optimal order of truncation and aliasing errors for multi-dimensional Whittaker-Shannon sampling expansion. - Pei-Xin Ye; Baohuai Sheng; Xiuhua Yuan (Int. J. Wirel. Mob. Comput., 2012)

Learning Rates of Support Vector Machine Classifiers with Data Dependent Hypothesis Spaces. - Baohuai Sheng; Pei-Xin Ye (J. Comput., 2012)

Strong Convex Loss Can Increase the Learning Rates of Online Learning. - Baohuai Sheng; Liqin Duan; Pei-Xin Ye (J. Comput., 2014)

Convergence rate of semi-supervised gradient learning algorithms. - Baohuai Sheng; Daohong Xiang; Peixin Ye (Int. J. Wavelets Multiresolution Inf. Process., 2015)

The performance of semi-supervised Laplacian regularized regression with the least square loss. - Baohuai Sheng; Daohong Xiang (Int. J. Wavelets Multiresolution Inf. Process., 2017)

The improved learning rate for regularized regression with RKBSs. - Huanxiang Liu; Baohuai Sheng; Peixin Ye (Int. J. Mach. Learn. Cybern., 2017)

The convergence rate of semi-supervised regression with quadratic loss. - Baohuai Sheng; Hancan Zhu (Appl. Math. Comput., 2018)

Convergence rate of SVM for kernel-based robust regression. - Shuhua Wang; Zhenlong Chen; Baohuai Sheng (Int. J. Wavelets Multiresolution Inf. Process., 2019)

Error analysis of the kernel regularized regression based on refined convex losses and RKBSs. - Baohuai Sheng; Lan Zuo (Int. J. Wavelets Multiresolution Inf. Process., 2021)

Some Upper Bounds for RKHS Approximation by Bessel Functions. - Mingdang Tian; Baohuai Sheng; Shuhua Wang (Axioms, 2022)

The kernel regularized learning algorithm for solving Laplace equation with Dirichlet boundary. - Baohuai Sheng; Dapao Zhou; Shuhua Wang (Int. J. Wavelets Multiresolution Inf. Process., 2022)

Error analysis of kernel regularized pairwise learning with a strongly convex loss. - Shuhua Wang; Baohuai Sheng (Math. Found. Comput., 2023)

On the density of translation networks defined on the unit ball. - Xiaojun Sun; Baohuai Sheng; Lin Liu; Xiaoling Pan (Math. Found. Comput., 2024)

Reproducing property of bounded linear operators and kernel regularized least square regressions. - Baohuai Sheng (Int. J. Wavelets Multiresolution Inf. Process., 2024)

Deterministic error analysis of kernel regularized regression for spherical scattered data. - Wan Li; Yeli Niu; Baohuai Sheng; Peixin Ye (Int. J. Wavelets Multiresolution Inf. Process., 2025)