Peixin Ye

According to our database, Peixin Ye authored at least 44 papers between 2003 and 2023.

Collaborative distances:

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

2023

A multi-point collaborative DDoS defense mechanism for IIoT environment.

Hongcheng Huang, Peixin Ye, Min Hu, Jun Wu

Digit. Commun. Networks, April, 2023

Efficiency of Orthogonal Matching Pursuit for Group Sparse Recovery.

Chunfang Shao, Xiujie Wei, Peixin Ye, Shuo Xing

Axioms, April, 2023

Optimality of the rescaled pure greedy learning algorithms.

Wenhui Zhang, Peixin Ye, Shuo Xing

Int. J. Wavelets Multiresolution Inf. Process., March, 2023

Approximation Properties of the Blending-Type Bernstein-Durrmeyer Operators.

Yu-Jie Liu, Wentao Cheng, Wen-Hui Zhang, Pei-Xin Ye

Axioms, January, 2023

2022

Unified error estimate for weak biorthogonal Greedy algorithms.

Bing Jiang, Peixin Ye, Wenhui Zhang

Int. J. Wavelets Multiresolution Inf. Process., 2022

Optimality of the Approximation and Learning by the Rescaled Pure Super Greedy Algorithms.

Wenhui Zhang, Peixin Ye, Shuo Xing, Xu Xu

Axioms, 2022

Almost Optimality of the Orthogonal Super Greedy Algorithm for μ-Coherent Dictionaries.

Chunfang Shao, Jincai Chang, Peixin Ye, Wenhui Zhang, Shuo Xing

Axioms, 2022

2021

Efficiency of the weak Rescaled Pure Greedy Algorithm.

Bing Jiang, Peixin Ye

Int. J. Wavelets Multiresolution Inf. Process., 2021

2020

Randomized approximation numbers on Besov classes with mixed smoothness.

Liqin Duan, Peixin Ye

Int. J. Wavelets Multiresolution Inf. Process., 2020

Error analysis of the moving least-squares regression learning algorithm with β-mixing and non-identical sampling.

Qin Guo, Peixin Ye

Int. J. Comput. Math., 2020

2019

Error analysis of the moving least-squares method with non-identical sampling.

Qin Guo, Peixin Ye

Int. J. Comput. Math., 2019

2018

Coefficient-based lq-regularized regression with indefinite kernels and unbounded sampling.

Qin Guo, Cheng Wang, Peixin Ye

J. Approx. Theory, 2018

Convergence Rate for l^q-Coefficient Regularized Regression With Non-i.i.d. Sampling.

Qin Guo, Peixin Ye, Binlei Cai

IEEE Access, 2018

Error Analysis of Least-Squares l^q-Regularized Regression Learning Algorithm With the Non-Identical and Dependent Samples.

Qin Guo, Peixin Ye

IEEE Access, 2018

2017

The improved learning rate for regularized regression with RKBSs.

Huanxiang Liu, Baohuai Sheng, Peixin Ye

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

Almost optimality of orthogonal super greedy algorithms for incoherent dictionaries.

Chunfang Shao, Peixin Ye

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

2016

Coefficient-based regularized regression with dependent and unbounded sampling.

Qin Guo, Peixin Ye

Int. J. Wavelets Multiresolution Inf. Process., 2016

2015

The efficiency of using Orthogonal Matching Pursuit in compressed sensing.

Peixin Ye, Xiujie Wei

J. Comput. Methods Sci. Eng., 2015

Improved bounds on restricted isometry constant for orthogonal multi matching pursuit.

Xiujie Wei, Peixin Ye

J. Comput. Methods Sci. Eng., 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

2013

Optimal error for Orthogonal Matching Pursuit for μ-coherent dictionaries.

Jingfan Long, Xiujie Wei, Peixin Ye

Proceedings of the Ninth International Conference on Natural Computation, 2013

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

Inverse Estimates for Lupas-Baskakov Operators.

Zhanjie Song, Peixin Ye

J. Comput., 2011

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

Baohuai Sheng, Pei-Xin Ye

J. Comput., 2011

Greedy approximation with regard to non-greedy bases.

Vladimir N. Temlyakov, Mingrui Yang, Peixin Ye

Adv. Comput. Math., 2011

Quadrature formula for some classes of analytic functions.

Peixin Ye

Proceedings of the International Conference on Electronic and Mechanical Engineering and Information Technology, 2011

2010

Monte Carlo integration with small random bits.

Sheng Zhang, Peixin Ye, Jingfan Long

Proceedings of the Sixth International Conference on Natural Computation, 2010

Convergence rate of quantum algorithm for multivariate approximation.

Jingfan Long, Sheng Zhang, Peixin Ye

Proceedings of the Sixth International Conference on Natural Computation, 2010

2008

Optimal integration error on anisotropic classes for restricted Monte Carlo and quantum algorithms.

Peixin Ye, Xiaofei Hu

J. Approx. Theory, 2008

Complexity of Functional Learning on Some Classes of Multivariate Functions.

Peixin Ye, Qing He

Proceedings of the Fourth International Conference on Natural Computation, 2008

Quantum Complexity of the Approximation on the Classes B(Wrp([0, 1]d)) and B(Hrp([0, 1]d)).

Peixin Ye

Proceedings of the Fourth International Conference on Natural Computation, 2008

Lower Bound for Quantum Integration Error on Some Sobolev Classes.

Peixin Ye

Proceedings of the Fourth International Conference on Natural Computation, 2008

An Adaptive Algorithm in m-Term Approximation for Some Multivariate Functions.

Peixin Ye, Zhiyong Zhao

Proceedings of the International Conference on Computer Science and Software Engineering, 2008

Restricted Monte Carlo Integration on Some Multivariate Functions.

Peixin Ye, Qing He

Proceedings of the International Conference on Computer Science and Software Engineering, 2008

Quantum Approximation on Some Classes of Multivarite Functions.

Peixin Ye

Proceedings of the International Conference on Computer Science and Software Engineering, 2008

2007

An Greedy-type Algorithm in m-term Approximation For Besov Class with Mixed Smoothness.

Peixin Ye, Qing He

Proceedings of the Third International Conference on Natural Computation, 2007

Quantum Approximation Error on Some Sobolev Classes.

Peixin Ye

Proceedings of the Third International Conference on Natural Computation, 2007

Quantum Integration Error on Some Classes of Multivariate Functions.

Peixin Ye, Qing He

Proceedings of the Advanced Intelligent Computing Theories and Applications. With Aspects of Contemporary Intelligent Computing Techniques, 2007

2006

Quantum Integration Error for Some Sobolev Classes.

Peixin Ye, Xiaofei Hu

Proceedings of the Advances in Natural Computation, Second International Conference, 2006

2005

Computational complexity of the integration problem for anisotropic classes.

Peixin Ye

Adv. Comput. Math., 2005

2003

Integration error for multivariate functions from anisotropic classes .

Gensun Fang, Peixin Ye

J. Complex., 2003

Probabilistic and average linear widths of Sobolev space with Gaussian measure.

Gensun Fang, Peixin Ye

J. Complex., 2003