Baohuai Sheng

According to our database, Baohuai Sheng authored at least 18 papers between 2007 and 2024.

Collaborative distances:

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

2024

Reproducing property of bounded linear operators and kernel regularized least square regressions.

Baohuai Sheng

Int. J. Wavelets Multiresolution Inf. Process., September, 2024

On the density of translation networks defined on the unit ball.

Xiaojun Sun, Baohuai Sheng, Lin Liu, Xiaoling Pan

Math. Found. Comput., 2024

2023

Error analysis of kernel regularized pairwise learning with a strongly convex loss.

Shuhua Wang, Baohuai Sheng

Math. Found. Comput., 2023

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

Some Upper Bounds for RKHS Approximation by Bessel Functions.

Mingdang Tian, Baohuai Sheng, Shuhua Wang

Axioms, 2022

2021

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

2019

Convergence rate of SVM for kernel-based robust regression.

Shuhua Wang, Zhenlong Chen, Baohuai Sheng

Int. J. Wavelets Multiresolution Inf. Process., 2019

2018

The convergence rate of semi-supervised regression with quadratic loss.

Baohuai Sheng, Hancan Zhu

Appl. Math. Comput., 2018

2017

The improved learning rate for regularized regression with RKBSs.

Huanxiang Liu, Baohuai Sheng, Peixin Ye

Int. J. Mach. Learn. Cybern., 2017

The performance of semi-supervised Laplacian regularized regression with the least square loss.

Baohuai Sheng, Daohong Xiang

Int. J. Wavelets Multiresolution Inf. Process., 2017

2015

Convergence rate of semi-supervised gradient learning algorithms.

Baohuai Sheng, Daohong Xiang, Peixin Ye

Int. J. Wavelets Multiresolution Inf. Process., 2015

2014

Strong Convex Loss Can Increase the Learning Rates of Online Learning.

Baohuai Sheng, Liqin Duan, Pei-Xin Ye

J. Comput., 2014

2012

Learning Rates of Support Vector Machine Classifiers with Data Dependent Hypothesis Spaces.

Baohuai Sheng, Pei-Xin Ye

J. Comput., 2012

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

2011

Least Square Regression Learning with Data Dependent Hypothesis and Coefficient Regularzation.

Baohuai Sheng, Pei-Xin Ye

J. Comput., 2011

2009

On Integrity of Harary Graphs.

Fengwei Li, Qingfang Ye, Baohuai Sheng

Proceedings of the Combinatorial Optimization and Applications, 2009

2008

The covering number for some Mercer kernel Hilbert spaces.

Baohuai Sheng, Jianli Wang, Ping Li

J. Complex., 2008

2007

On Approximation By Reproducing Kernel Spaces in Weighted L^p Spaces.

Baohuai Sheng

J. Syst. Sci. Complex., 2007