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Wei Wang
492 publications
Yong Liu
227 publications
Lu Zhang
137 publications
Deyu Meng
103 publications
Hui Zhang
85 publications
Jing Dong
67 publications
Tao Sun
57 publications
Yi Chen
52 publications
Tao Luo
51 publications
Yue Li
44 publications
Zhi-Qin John Xu
43 publications

∙ 08/16/2023

Phase Retrieval with Background Information: Decreased References and Efficient Methods

Fourier phase retrieval(PR) is a severely ill-posed inverse problem that...

0 Ziyang Yuan, et al. ∙

∙ 07/16/2023

Untrained neural network embedded Fourier phase retrieval from few measurements

Fourier phase retrieval (FPR) is a challenging task widely used in vario...

0 Liyuan Ma, et al. ∙

∙ 06/12/2023

A Weighted Randomized Sparse Kaczmarz Method for Solving Linear Systems

The randomized sparse Kaczmarz method, designed for seeking the sparse s...

0 Lu Zhang, et al. ∙

∙ 03/27/2023

Regularize implicit neural representation by itself

This paper proposes a regularizer called Implicit Neural Representation ...

0 Zhemin Li, et al. ∙

∙ 08/11/2022

Adaptive and Implicit Regularization for Matrix Completion

The explicit low-rank regularization, e.g., nuclear norm regularization,...

33 Zhemin Li, et al. ∙

∙ 12/29/2021

Adaptively Sketched Bregman Projection Methods for Linear Systems

The sketch-and-project, as a general archetypal algorithm for solving li...

0 Ziyang Yuan, et al. ∙

∙ 10/12/2021

AIR-Net: Adaptive and Implicit Regularization Neural Network for Matrix Completion

Conventionally, the matrix completion (MC) model aims to recover a matri...

0 Zhemin Li, et al. ∙

∙ 03/16/2021

A survey of deep neural network watermarking techniques

Protecting the Intellectual Property Rights (IPR) associated to Deep Neu...

0 Yue Li, et al. ∙

∙ 01/13/2021

Sparse Sampling Kaczmarz-Motzkin Method with Linear Convergence

The randomized sparse Kaczmarz method was recently proposed to recover s...

0 Ziyang Yuan, et al. ∙

∙ 09/28/2020

RoGAT: a robust GNN combined revised GAT with adjusted graphs

Graph Neural Networks(GNNs) are useful deep learning models to deal with...

0 Xianchen Zhou, et al. ∙

∙ 07/29/2020

A regularized deep matrix factorized model of matrix completion for image restoration

It has been an important approach of using matrix completion to perform ...

0 Zhemin Li, et al. ∙

∙ 04/18/2018

An Improved Reversible Data Hiding Scheme by Changing Modification Direction of Partial Coefficients in JPEG Images

This paper first reviews the reversible data hiding scheme, of Liu et al...

0 Yi Chen, et al. ∙

∙ 04/18/2018

A Novel Reversible Data Hiding Employing All Quantized Nonzero AC Coefficients in JPEG Images

This paper revisits the reversible data hiding scheme, of Liu et al. in ...

0 Yi Chen, et al. ∙

∙ 04/18/2018

Reversible Video Data Hiding Using Zero QDCT Coefficient-Pairs

There exist many zero quantized discrete cosine transform (QDCT) coeffic...

0 Yi Chen, et al. ∙

∙ 04/03/2018

Intra-Frame Error Concealment Scheme using 3D Reversible Data Hiding in Mobile Cloud Environment

Data in mobile cloud environment are mainly transmitted via wireless noi...

0 Yanli Chen, et al. ∙

∙ 02/20/2018

The Cut and Dominating Set Problem in A Steganographer Network

A steganographer network corresponds to a graphic structure that the inv...

0 Hanzhou Wu, et al. ∙

∙ 02/05/2018

Phase retrieval with background information

Phase retrieval problem has been studied in various applications. It is ...

0 Ziyang Yuan, et al. ∙

∙ 01/15/2018

Reversible Embedding to Covers Full of Boundaries

In reversible data embedding, to avoid overflow and underflow problem, b...

0 Hanzhou Wu, et al. ∙

∙ 01/15/2018

Ensemble Reversible Data Hiding

The conventional reversible data hiding (RDH) algorithms often consider ...

0 Hanzhou Wu, et al. ∙

∙ 12/11/2017

A Graph-theoretic Model to Steganography on Social Networks

Steganography aims to conceal the very fact that the communication takes...

0 Hanzhou Wu, et al. ∙

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