Di-Rong Chen

According to our database, Di-Rong Chen authored at least 40 papers between 2000 and 2024.

Collaborative distances:

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

2024

Wavelet-based neural network model for track stiffness signal detection.

Yunlong Ding, Di-Rong Chen

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

2023

Approximation of Nonlinear Functionals Using Deep ReLU Networks.

Linhao Song, Jun Fan, Di-Rong Chen, Ding-Xuan Zhou

CoRR, 2023

2022

Framelet block thresholding estimator for sparse functional data.

Di-Rong Chen, Kun Cheng, Chao Liu

J. Multivar. Anal., 2022

2021

Estimations of singular functions of kernel cross-covariance operators.

Heng Chen, Di-Rong Chen, Yao Zhao

J. Approx. Theory, 2021

2019

A class of optimal estimators for the covariance operator in reproducing kernel Hilbert spaces.

Yang Zhou, Di-Rong Chen, Wei Huang

J. Multivar. Anal., 2019

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

Simultaneous estimations of optimal directions and optimal transformations for functional data.

Heng Chen, Wei Huang, Di-Rong Chen

Int. J. Wavelets Multiresolution Inf. Process., 2018

Generalization error bound of semi-supervised learning with ℓ¹ regularization in sum space.

Chao Liu, Di-Rong Chen

Neurocomputing, 2018

Interpretable Functional Logistic Regression.

Cui Lv, Di-Rong Chen

Proceedings of the 2nd International Conference on Computer Science and Application Engineering, 2018

2016

Recovery of Low Rank Symmetric Matrices via Schatten p Norm Minimization.

Li Cui, Lu Liu, Di-Rong Chen, Jianfeng Xie

Asia Pac. J. Oper. Res., 2016

2015

Convergence of ℓ_2/3 Regularization for Sparse Signal Recovery.

Lu Liu, Di-Rong Chen

Asia Pac. J. Oper. Res., 2015

2014

Learning with Convex Loss and Indefinite Kernels.

Hongzhi Tong, Di-Rong Chen, Fenghong Yang

Neural Comput., 2014

Exact minimum rank approximation via Schatten p-norm minimization.

Lu Liu, Wei Huang, Di-Rong Chen

J. Comput. Appl. Math., 2014

Learning rate of support vector machine for ranking.

Heng Chen, Di-Rong Chen

J. Approx. Theory, 2014

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

2013

Least Square Regularized Regression in Sum Space.

Yong-Li Xu, Di-Rong Chen, Han-Xiong Li, Lu Liu

IEEE Trans. Neural Networks Learn. Syst., 2013

The Improved Bounds of Restricted Isometry Constant for Recovery via ℓ_p-Minimization.

Rui Wu, Di-Rong Chen

IEEE Trans. Inf. Theory, 2013

The Exact Support Recovery of Sparse Signals With Noise via Orthogonal Matching Pursuit.

Rui Wu, Wei Huang, Di-Rong Chen

IEEE Signal Process. Lett., 2013

Learning Rates for l¹-Regularized Kernel Classifiers.

Hongzhi Tong, Di-Rong Chen, Fenghong Yang

J. Appl. Math., 2013

2012

Support vector machines regression with I¹-regularizer.

Hongzhi Tong, Di-Rong Chen, Fenghong Yang

J. Approx. Theory, 2012

The coefficient Regularized Regression with Random Projection.

Di-Rong Chen, Han Li

Int. J. Wavelets Multiresolution Inf. Process., 2012

On the performance of regularized regression learning in Hilbert space.

Di-Rong Chen, Han Li

Neurocomputing, 2012

2011

Projected gradient iteration for nonlinear operator equation.

Wei Huang, Di-Rong Chen

J. Comput. Appl. Math., 2011

Wavelet shrinkage estimators of Hilbert transform.

Di-Rong Chen, Yao Zhao

J. Approx. Theory, 2011

2010

Least Square Regression with <i>l^p</i>-Coefficient Regularization.

Hongzhi Tong, Di-Rong Chen, Fenghong Yang

Neural Comput., 2010

Convergence of irregular Hermite subdivision schemes.

Yao Zhao, Di-Rong Chen

Comput. Aided Geom. Des., 2010

2009

Partially-Linear Least-Squares Regularized Regression for System Identification.

Yong-Li Xu, Di-Rong Chen

IEEE Trans. Autom. Control., 2009

Learning Rates of Regularized Regression for Functional Data.

Yong-Li Xu, Di-Rong Chen

Int. J. Wavelets Multiresolution Inf. Process., 2009

Analysis of Support Vector Machines Regression.

Hongzhi Tong, Di-Rong Chen, Lizhong Peng

Found. Comput. Math., 2009

2008

Learning rates for regularized classifiers using multivariate polynomial kernels.

Hongzhi Tong, Di-Rong Chen, Lizhong Peng

J. Complex., 2008

Wavelet Denoising for Differential Operator.

Hongtao Meng, Di-Rong Chen, Yao Zhao

Proceedings of the 2008 International Conference on Scientific Computing, 2008

2007

A Construction of convergent Cascade Algorithms in Sobolev Spaces.

Di-Rong Chen

Int. J. Wavelets Multiresolution Inf. Process., 2007

2006

Consistency of Multiclass Empirical Risk Minimization Methods Based on Convex Loss.

Di-Rong Chen, Tao Sun

J. Mach. Learn. Res., 2006

The consistency of multicategory support vector machines.

Di-Rong Chen, Dao-Hong Xiang

Adv. Comput. Math., 2006

2004

Support Vector Machine Soft Margin Classifiers: Error Analysis.

Di-Rong Chen, Qiang Wu, Yiming Ying, Ding-Xuan Zhou

J. Mach. Learn. Res., 2004

2003

Shift-invariant spaces of tempered distributions and Lp-functions.

Di-Rong Chen

J. Approx. Theory, 2003

2002

Construction of Smooth Refinable Function Vectors by Cascade Algorithms.

Di-Rong Chen

SIAM J. Numer. Anal., 2002

Convergence of Cascade Algorithms in Sobolev Spaces for Perturbed Refinement Masks.

Di-Rong Chen, Gerlind Plonka

J. Approx. Theory, 2002

2000

On the Splitting Trick and Wavelet Frame Packets.

Di-Rong Chen

SIAM J. Math. Anal., 2000

Construction of multivariate biorthogonal wavelets with arbitrary vanishing moments.

Di-Rong Chen, Bin Han, Sherman D. Riemenschneider

Adv. Comput. Math., 2000