Construction of multivariate biorthogonal wavelets with arbitrary vanishing moments. - Di-Rong Chen; Bin Han 003; Sherman D. Riemenschneider (Adv. Comput. Math., 2000)

On the Splitting Trick and Wavelet Frame Packets. - Di-Rong Chen (SIAM J. Math. Anal., 2000)

Convergence of Cascade Algorithms in Sobolev Spaces for Perturbed Refinement Masks. - Di-Rong Chen; Gerlind Plonka (J. Approx. Theory, 2002)

Construction of Smooth Refinable Function Vectors by Cascade Algorithms. - Di-Rong Chen (SIAM J. Numer. Anal., 2002)

Shift-invariant spaces of tempered distributions and Lp-functions. - Di-Rong Chen (J. Approx. Theory, 2003)

Support Vector Machine Soft Margin Classifiers: Error Analysis. - Di-Rong Chen; Qiang Wu 003; Yiming Ying; Ding-Xuan Zhou (J. Mach. Learn. Res., 2004)

The consistency of multicategory support vector machines. - Di-Rong Chen; Dao-Hong Xiang (Adv. Comput. Math., 2006)

Consistency of Multiclass Empirical Risk Minimization Methods Based on Convex Loss. - Di-Rong Chen; Tao Sun (J. Mach. Learn. Res., 2006)

A Construction of convergent Cascade Algorithms in Sobolev Spaces. - Di-Rong Chen (Int. J. Wavelets Multiresolution Inf. Process., 2007)

Wavelet Denoising for Differential Operator. - Hongtao Meng; Di-Rong Chen; Yao Zhao (CSC, 2008)

Learning rates for regularized classifiers using multivariate polynomial kernels. - Hongzhi Tong; Di-Rong Chen; Lizhong Peng (J. Complex., 2008)

Analysis of Support Vector Machines Regression. - Hongzhi Tong; Di-Rong Chen; Lizhong Peng (Found. Comput. Math., 2009)

Learning Rates of Regularized Regression for Functional Data. - Yong-Li Xu; Di-Rong Chen (Int. J. Wavelets Multiresolution Inf. Process., 2009)

Partially-Linear Least-Squares Regularized Regression for System Identification. - Yong-Li Xu; Di-Rong Chen (IEEE Trans. Autom. Control., 2009)

Convergence of irregular Hermite subdivision schemes. - Yao Zhao; Di-Rong Chen (Comput. Aided Geom. Des., 2010)

Least Square Regression with lp-Coefficient Regularization. - Hongzhi Tong; Di-Rong Chen; Fenghong Yang (Neural Comput., 2010)

Wavelet shrinkage estimators of Hilbert transform. - Di-Rong Chen; Yao Zhao (J. Approx. Theory, 2011)

Projected gradient iteration for nonlinear operator equation. - Wei Huang; Di-Rong Chen (J. Comput. Appl. Math., 2011)

On the performance of regularized regression learning in Hilbert space. - Di-Rong Chen; Han Li (Neurocomputing, 2012)

The coefficient Regularized Regression with Random Projection. - Di-Rong Chen; Han Li (Int. J. Wavelets Multiresolution Inf. Process., 2012)

Support vector machines regression with I1-regularizer. - Hongzhi Tong; Di-Rong Chen; Fenghong Yang (J. Approx. Theory, 2012)

Learning Rates for l1-Regularized Kernel Classifiers. - Hongzhi Tong; Di-Rong Chen; Fenghong Yang (J. Appl. Math., 2013)

The Exact Support Recovery of Sparse Signals With Noise via Orthogonal Matching Pursuit. - Rui Wu; Wei Huang 020; Di-Rong Chen (IEEE Signal Process. Lett., 2013)

The Improved Bounds of Restricted Isometry Constant for Recovery via ℓp-Minimization. - Rui Wu; Di-Rong Chen (IEEE Trans. Inf. Theory, 2013)

Least Square Regularized Regression in Sum Space. - Yong-Li Xu; Di-Rong Chen; Han-Xiong Li; Lu Liu 010 (IEEE Trans. Neural Networks Learn. Syst., 2013)

ℓ1-Norm support vector machine for ranking with exponentially strongly mixing sequence. - Di-Rong Chen; Shou-You Huang (Int. J. Wavelets Multiresolution Inf. Process., 2014)

Learning rate of support vector machine for ranking. - Heng Chen; Di-Rong Chen (J. Approx. Theory, 2014)

Exact minimum rank approximation via Schatten p-norm minimization. - Lu Liu 010; Wei Huang 020; Di-Rong Chen (J. Comput. Appl. Math., 2014)

Learning with Convex Loss and Indefinite Kernels. - Hongzhi Tong; Di-Rong Chen; Fenghong Yang (Neural Comput., 2014)

Convergence of ℓ2/3 Regularization for Sparse Signal Recovery. - Lu Liu 010; Di-Rong Chen (Asia Pac. J. Oper. Res., 2015)

Recovery of Low Rank Symmetric Matrices via Schatten p Norm Minimization. - Li Cui; Lu Liu 010; Di-Rong Chen; Jianfeng Xie (Asia Pac. J. Oper. Res., 2016)

Interpretable Functional Logistic Regression. - Cui Lv; Di-Rong Chen (CSAE, 2018)

Generalization error bound of semi-supervised learning with ℓ1 regularization in sum space. - Chao Liu; Di-Rong Chen (Neurocomputing, 2018)

Simultaneous estimations of optimal directions and optimal transformations for functional data. - Heng Chen; Wei Huang 020; Di-Rong Chen (Int. J. Wavelets Multiresolution Inf. Process., 2018)

Learning Rates of Regularized Regression With Multiple Gaussian Kernels for Multi-Task Learning. - Yong-Li Xu; Xiao-Xing Li; Di-Rong Chen; Han-Xiong Li (IEEE Trans. Neural Networks Learn. Syst., 2018)

A class of optimal estimators for the covariance operator in reproducing kernel Hilbert spaces. - Yang Zhou; Di-Rong Chen; Wei Huang 020 (J. Multivar. Anal., 2019)

Estimations of singular functions of kernel cross-covariance operators. - Heng Chen; Di-Rong Chen; Yao Zhao (J. Approx. Theory, 2021)

Framelet block thresholding estimator for sparse functional data. - Di-Rong Chen; Kun Cheng; Chao Liu (J. Multivar. Anal., 2022)

Approximation of Nonlinear Functionals Using Deep ReLU Networks. - Linhao Song; Jun Fan; Di-Rong Chen; Ding-Xuan Zhou (CoRR, 2023)

Wavelet-based neural network model for track stiffness signal detection. - Yunlong Ding; Di-Rong Chen (Int. J. Wavelets Multiresolution Inf. Process., 2024)

Regularized reduced-rank regression for structured output prediction. - Heng Chen; Di-Rong Chen; Kun Cheng; Yang Zhou (J. Complex., 2026)