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Universality of deep convolutional neural networks

Applied and computational harmonic analysis, 2020-03, Vol.48 (2), p.787-794

Zhou, Ding-Xuan

2020

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Theory of deep convolutional neural networks: Downsampling

Neural networks, 2020-04, Vol.124, p.319-327

Zhou, Ding-Xuan

2020

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Deep distributed convolutional neural networks: Universality

Analysis and applications, 2018-11, Vol.16 (6), p.895-919

Zhou, Ding-Xuan

2018

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Learning Theory: An Approximation Theory Viewpoint

1, 2007

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Generalization Analysis of CNNs for Classification on Spheres

IEEE transaction on neural networks and learning systems, 2023-09, Vol.34 (9), p.6200-6213

2023

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Data-Dependent Generalization Bounds for Multi-Class Classification

IEEE transactions on information theory, 2019-05, Vol.65 (5), p.2995-3021

2019

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Theory of deep convolutional neural networks III: Approximating radial functions

Neural networks, 2021-12, Vol.144, p.778-790

2021

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Approximation of functions from Korobov spaces by shallow neural networks

Information sciences, 2024-06, Vol.670, p.120573, Article 120573

2024

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Depth Selection for Deep ReLU Nets in Feature Extraction and Generalization

IEEE transactions on pattern analysis and machine intelligence, 2022-04, Vol.44 (4), p.1853-1868

2022

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Distributed kernel gradient descent algorithm for minimum error entropy principle

Applied and computational harmonic analysis, 2020-07, Vol.49 (1), p.229-256

2020

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SignReLU neural network and its approximation ability

Journal of computational and applied mathematics, 2024-04, Vol.440, p.115551, Article 115551

2024

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MINIMAX OPTIMAL RATES OF ESTIMATION IN HIGH DIMENSIONAL ADDITIVE MODELS

The Annals of statistics, 2016-12, Vol.44 (6), p.2564-2593

2016

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Generalization Analysis of Pairwise Learning for Ranking With Deep Neural Networks

Neural computation, 2023-05, Vol.35 (6), p.1135-1158

2023

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Universal Consistency of Deep Convolutional Neural Networks

IEEE transactions on information theory, 2022-07, Vol.68 (7), p.4610-4617

2022

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Online Learning Algorithms Can Converge Comparably Fast as Batch Learning

IEEE transaction on neural networks and learning systems, 2018-06, Vol.29 (6), p.2367-2378

2018

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Approximating functions with multi-features by deep convolutional neural networks

Analysis and applications, 2023-01, Vol.21 (1), p.93-125

2023

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Derivative reproducing properties for kernel methods in learning theory

Journal of computational and applied mathematics, 2008-10, Vol.220 (1-2), p.456-463

ZHOU, Ding-Xuan

2008

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Unregularized online learning algorithms with general loss functions

Applied and computational harmonic analysis, 2017-03, Vol.42 (2), p.224-244

2017

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Learning theory of distributed spectral algorithms

Inverse problems, 2017-07, Vol.33 (7), p.74009

2017

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Distributed Kernel-Based Gradient Descent Algorithms

Constructive approximation, 2018-04, Vol.47 (2), p.249-276

2018

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Convergence of Gradient Descent for Minimum Error Entropy Principle in Linear Regression

IEEE transactions on signal processing, 2016-12, Vol.64 (24), p.6571-6579

2016

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Image encryption using exclusive-OR with DNA complementary rules and double random phase encoding

Physics letters. A, 2019-02, Vol.383 (9), p.915-922

2019

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Rates of approximation by ReLU shallow neural networks

Journal of Complexity, 2023-12, Vol.79, p.101784, Article 101784

2023

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Online Pairwise Learning Algorithms

Neural computation, 2016-04, Vol.28 (4), p.743-777

2016

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Novel Dibenzofulvene‐Based NIR‐II Emission Phototheranostic Agent with an 82.6% Photothermal Conversion Efficiency for Photothermal Therapy

Advanced functional materials, 2024-02, Vol.34 (8), p.n/a

2024

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Universality of deep convolutional neural networks

Theory of deep convolutional neural networks: Downsampling

Deep distributed convolutional neural networks: Universality

Learning Theory: An Approximation Theory Viewpoint

Generalization Analysis of CNNs for Classification on Spheres

Data-Dependent Generalization Bounds for Multi-Class Classification

Theory of deep convolutional neural networks III: Approximating radial functions

Approximation of functions from Korobov spaces by shallow neural networks

Depth Selection for Deep ReLU Nets in Feature Extraction and Generalization

Distributed kernel gradient descent algorithm for minimum error entropy principle

SignReLU neural network and its approximation ability

MINIMAX OPTIMAL RATES OF ESTIMATION IN HIGH DIMENSIONAL ADDITIVE MODELS

Generalization Analysis of Pairwise Learning for Ranking With Deep Neural Networks

Universal Consistency of Deep Convolutional Neural Networks

Online Learning Algorithms Can Converge Comparably Fast as Batch Learning

Approximating functions with multi-features by deep convolutional neural networks

Derivative reproducing properties for kernel methods in learning theory

Unregularized online learning algorithms with general loss functions

Learning theory of distributed spectral algorithms

Distributed Kernel-Based Gradient Descent Algorithms

Convergence of Gradient Descent for Minimum Error Entropy Principle in Linear Regression

Image encryption using exclusive-OR with DNA complementary rules and double random phase encoding

Rates of approximation by ReLU shallow neural networks

Online Pairwise Learning Algorithms

Novel Dibenzofulvene‐Based NIR‐II Emission Phototheranostic Agent with an 82.6% Photothermal Conversion Efficiency for Photothermal Therapy

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