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Theory of Deep Convolutional Neural Networks II: Spherical Analysis

Jul 28, 2020
Zhiying Fang, Han Feng, Shuo Huang, Ding-Xuan Zhou


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Depth Selection for Deep ReLU Nets in Feature Extraction and Generalization

Apr 01, 2020
Zhi Han, Siquan Yu, Shao-Bo Lin, Ding-Xuan Zhou

* 19 pages 

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Distributed Kernel Ridge Regression with Communications

Mar 27, 2020
Shao-Bo Lin, Di Wang, Ding-Xuan Zhou

* 38pages 

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Realization of spatial sparseness by deep ReLU nets with massive data

Dec 16, 2019
Charles K. Chui, Shao-Bo Lin, Bo Zhang, Ding-Xuan Zhou

* 15pages, 4 figures 

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Fast Polynomial Kernel Classification for Massive Data

Dec 06, 2019
Jinshan Zeng, Minrun Wu, Shao-Bo Lin, Ding-Xuan Zhou

* arXiv admin note: text overlap with arXiv:1402.4735 by other authors 

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Towards Understanding the Spectral Bias of Deep Learning

Dec 03, 2019
Yuan Cao, Zhiying Fang, Yue Wu, Ding-Xuan Zhou, Quanquan Gu

* 26 pages, 4 figures 

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Distributed filtered hyperinterpolation for noisy data on the sphere

Oct 06, 2019
Shao-Bo Lin, Yu Guang Wang, Ding-Xuan Zhou

* 26 pages, 4 figures 

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Deep Neural Networks for Rotation-Invariance Approximation and Learning

Apr 03, 2019
Charles K. Chui, Shao-Bo Lin, Ding-Xuan Zhou

* 34 pages, 1 figure 

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Universality of Deep Convolutional Neural Networks

Jul 20, 2018
Ding-Xuan Zhou


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Construction of neural networks for realization of localized deep learning

Mar 09, 2018
Charles K. Chui, Shao-Bo Lin, Ding-Xuan Zhou

* 22pages 

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Convergence of Online Mirror Descent Algorithms

Feb 18, 2018
Yunwen Lei, Ding-Xuan Zhou


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Data-dependent Generalization Bounds for Multi-class Classification

Dec 29, 2017
Yunwen Lei, Urun Dogan, Ding-Xuan Zhou, Marius Kloft


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Total stability of kernel methods

Sep 22, 2017
Andreas Christmann, Daohong Xiang, Ding-Xuan Zhou


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Distributed learning with regularized least squares

Mar 11, 2017
Shao-Bo Lin, Xin Guo, Ding-Xuan Zhou

* 28 pages 

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On the Robustness of Regularized Pairwise Learning Methods Based on Kernels

Oct 12, 2015
Andreas Christmann, Ding-Xuan Zhou

* 36 pages, 1 figure 

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Unregularized Online Learning Algorithms with General Loss Functions

Apr 26, 2015
Yiming Ying, Ding-Xuan Zhou


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Iterative Regularization for Learning with Convex Loss Functions

Apr 01, 2015
Junhong Lin, Lorenzo Rosasco, Ding-Xuan Zhou


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Minimax Optimal Rates of Estimation in High Dimensional Additive Models: Universal Phase Transition

Mar 10, 2015
Ming Yuan, Ding-Xuan Zhou


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Online Pairwise Learning Algorithms with Kernels

Feb 25, 2015
Yiming Ying, Ding-Xuan Zhou


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Consistency Analysis of an Empirical Minimum Error Entropy Algorithm

Dec 17, 2014
Jun Fan, Ting Hu, Qiang Wu, Ding-Xuan Zhou


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Learning rates for the risk of kernel based quantile regression estimators in additive models

May 14, 2014
Andreas Christmann, Ding-Xuan Zhou

* 35 pages, 2 figures 

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Learning Theory Approach to Minimum Error Entropy Criterion

Feb 22, 2013
Ting Hu, Jun Fan, Qiang Wu, Ding-Xuan Zhou

* JMLR 2013 

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