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Ding-Xuan Zhou
Titel
Zitiert von
Zitiert von
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Learning theory: an approximation theory viewpoint
F Cucker, DX Zhou
Cambridge University Press, 2007
10172007
Learning theory estimates via integral operators and their approximations
S Smale, DX Zhou
Constructive approximation 26 (2), 153-172, 2007
7452007
Universality of deep convolutional neural networks
DX Zhou
Applied and computational harmonic analysis 48 (2), 787-794, 2020
7352020
The covering number in learning theory
DX Zhou
Journal of Complexity 18 (3), 739-767, 2002
4122002
Estimating the approximation error in learning theory
S Smale, DX Zhou
Analysis and Applications 1 (01), 17-41, 2003
3172003
Support vector machine soft margin classifiers: error analysis
DR Chen, Q Wu, Y Ying, DX Zhou
The Journal of Machine Learning Research 5, 1143-1175, 2004
3162004
Shannon sampling and function reconstruction from point values
S Smale, DX Zhou
Bulletin of the American Mathematical Society 41 (3), 279-305, 2004
3022004
Capacity of reproducing kernel spaces in learning theory
DX Zhou
IEEE Transactions on information theory 49 (7), 1743-1752, 2003
2972003
Learning rates of least-square regularized regression
Q Wu, Y Ying, DX Zhou
Foundations of computational mathematics 6, 171-192, 2006
2862006
Theory of deep convolutional neural networks: Downsampling
DX Zhou
Neural Networks 124, 319-327, 2020
2612020
Shannon sampling II: Connections to learning theory
S Smale, DX Zhou
Applied and Computational Harmonic Analysis 19 (3), 285-302, 2005
2602005
Towards understanding the spectral bias of deep learning
Y Cao, Z Fang, Y Wu, DX Zhou, Q Gu
arXiv preprint arXiv:1912.01198, 2019
2472019
Distributed learning with regularized least squares
SB Lin, X Guo, DX Zhou
Journal of Machine Learning Research 18 (92), 1-31, 2017
2342017
SVM soft margin classifiers: linear programming versus quadratic programming
Q Wu, DX Zhou
Neural computation 17 (5), 1160-1187, 2005
2272005
Multi-kernel regularized classifiers
Q Wu, Y Ying, DX Zhou
Journal of Complexity 23 (1), 108-134, 2007
2142007
Derivative reproducing properties for kernel methods in learning theory
DX Zhou
Journal of computational and Applied Mathematics 220 (1-2), 456-463, 2008
2002008
Online learning with Markov sampling
S Smale, DX Zhou
Analysis and Applications 7 (01), 87-113, 2009
1762009
Deep distributed convolutional neural networks: Universality
DX Zhou
Analysis and applications 16 (06), 895-919, 2018
1652018
Approximation with polynomial kernels and SVM classifiers
DX Zhou, K Jetter
Advances in Computational Mathematics 25 (1), 323-344, 2006
1542006
Analysis of support vector machine classification.
Q Wu, DX Zhou
Journal of Computational Analysis & Applications 8 (2), 2006
1532006
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