Probabilistic and average linear widths of Sobolev space with Gaussian measure. - Gensun Fang; Peixin Ye (J. Complex., 2003)

Integration error for multivariate functions from anisotropic classes . - Gensun Fang; Peixin Ye (J. Complex., 2003)

Computational complexity of the integration problem for anisotropic classes. - Peixin Ye (Adv. Comput. Math., 2005)

Quantum Integration Error for Some Sobolev Classes. - Peixin Ye; Xiaofei Hu (ICNC (2), 2006)

Quantum Integration Error on Some Classes of Multivariate Functions. - Peixin Ye; Qing He (ICIC (3), 2007)

Quantum Approximation Error on Some Sobolev Classes. - Peixin Ye (ICNC (4), 2007)

An Greedy-type Algorithm in m-term Approximation For Besov Class with Mixed Smoothness. - Peixin Ye; Qing He (ICNC (1), 2007)

Quantum Approximation on Some Classes of Multivarite Functions. - Peixin Ye (CSSE (1), 2008)

Restricted Monte Carlo Integration on Some Multivariate Functions. - Peixin Ye; Qing He (CSSE (1), 2008)

An Adaptive Algorithm in m-Term Approximation for Some Multivariate Functions. - Peixin Ye; Zhiyong Zhao (CSSE (1), 2008)

Lower Bound for Quantum Integration Error on Some Sobolev Classes. - Peixin Ye (ICNC (3), 2008)

Quantum Complexity of the Approximation on the Classes B(Wrp([0, 1]d)) and B(Hrp([0, 1]d)). - Peixin Ye (ICNC (3), 2008)

Complexity of Functional Learning on Some Classes of Multivariate Functions. - Peixin Ye; Qing He (ICNC (3), 2008)

Optimal integration error on anisotropic classes for restricted Monte Carlo and quantum algorithms. - Peixin Ye; Xiaofei Hu (J. Approx. Theory, 2008)

Convergence rate of quantum algorithm for multivariate approximation. - Jingfan Long; Sheng Zhang 017; Peixin Ye (ICNC, 2010)

Monte Carlo integration with small random bits. - Sheng Zhang 017; Peixin Ye; Jingfan Long (ICNC, 2010)

Quadrature formula for some classes of analytic functions. - Peixin Ye (EMEIT, 2011)

Greedy approximation with regard to non-greedy bases. - Vladimir N. Temlyakov; Mingrui Yang; Peixin Ye (Adv. Comput. Math., 2011)

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

Inverse Estimates for Lupas-Baskakov Operators. - Zhanjie Song; Peixin 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)

Optimal error for Orthogonal Matching Pursuit for μ-coherent dictionaries. - Jingfan Long; Xiujie Wei; Peixin Ye (ICNC, 2013)

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)

Improved bounds on restricted isometry constant for orthogonal multi matching pursuit. - Xiujie Wei; Peixin Ye (J. Comput. Methods Sci. Eng., 2015)

The efficiency of using Orthogonal Matching Pursuit in compressed sensing. - Peixin Ye; Xiujie Wei (J. Comput. Methods Sci. Eng., 2015)

Coefficient-based regularized regression with dependent and unbounded sampling. - Qin Guo; Peixin Ye (Int. J. Wavelets Multiresolution Inf. Process., 2016)

Almost optimality of orthogonal super greedy algorithms for incoherent dictionaries. - Chunfang Shao; Peixin Ye (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)

Error Analysis of Least-Squares lq-Regularized Regression Learning Algorithm With the Non-Identical and Dependent Samples. - Qin Guo; Peixin Ye (IEEE Access, 2018)

Convergence Rate for lq-Coefficient Regularized Regression With Non-i.i.d. Sampling. - Qin Guo; Peixin Ye; Binlei Cai (IEEE Access, 2018)

Coefficient-based lq-regularized regression with indefinite kernels and unbounded sampling. - Qin Guo; Cheng Wang; Peixin Ye (J. Approx. Theory, 2018)

Error analysis of the moving least-squares method with non-identical sampling. - Qin Guo; Peixin Ye (Int. J. Comput. Math., 2019)

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)

Randomized approximation numbers on Besov classes with mixed smoothness. - Liqin Duan; Peixin Ye (Int. J. Wavelets Multiresolution Inf. Process., 2020)

Efficiency of the weak Rescaled Pure Greedy Algorithm. - Bing Jiang; Peixin Ye (Int. J. Wavelets Multiresolution Inf. Process., 2021)

Almost Optimality of the Orthogonal Super Greedy Algorithm for μ-Coherent Dictionaries. - Chunfang Shao; Jincai Chang; Peixin Ye; Wenhui Zhang 004; Shuo Xing (Axioms, 2022)

Optimality of the Approximation and Learning by the Rescaled Pure Super Greedy Algorithms. - Wenhui Zhang 004; Peixin Ye; Shuo Xing; Xu Xu (Axioms, 2022)

Unified error estimate for weak biorthogonal Greedy algorithms. - Bing Jiang; Peixin Ye; Wenhui Zhang 004 (Int. J. Wavelets Multiresolution Inf. Process., 2022)

Approximation Properties of the Blending-Type Bernstein-Durrmeyer Operators. - Yu-Jie Liu; Wentao Cheng; Wen-Hui Zhang 004; Pei-Xin Ye (Axioms, 2023)

Optimality of the rescaled pure greedy learning algorithms. - Wenhui Zhang 004; Peixin Ye; Shuo Xing (Int. J. Wavelets Multiresolution Inf. Process., 2023)

Efficiency of Orthogonal Matching Pursuit for Group Sparse Recovery. - Chunfang Shao; Xiujie Wei; Peixin Ye; Shuo Xing (Axioms, 2023)

A multi-point collaborative DDoS defense mechanism for IIoT environment. - Hongcheng Huang; Peixin Ye; Min Hu; Jun Wu (Digit. Commun. Networks, 2023)

Sparse Signal Recovery via Rescaled Matching Pursuit. - Wan Li; Peixin Ye (Axioms, 2024)

Approximation properties of some vector weak biorthogonal greedy algorithms. - Xianhe Wang; Xu Xu; Peixin Ye; Wenhui Zhang 004 (Int. J. Wavelets Multiresolution Inf. Process., 2024)

Error bounds of Approximate Weak Rescaled Pure Greedy Algorithms. - Bing Jiang; Peixin Ye; Wan Li; Man Lu (Int. J. Wavelets Multiresolution Inf. Process., 2025)

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)

Optimal restricted Monte Carlo integration on generalized Hölder classes. - Wan Li; Man Lu; Peixin Ye (J. Appl. Math. Comput., 2025)