Jianjun Wang

Affiliations:
  • Southwest University, College of Artificial Intelligence, Chongqing, China
  • Southwest University, School of Mathematics and Statistics, Chongqing, China
  • Xi'an Jiaotong University, Institute for Information and System Science, China (PhD 2006)


According to our database1, Jianjun Wang authored at least 80 papers between 2004 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
Low-tubal-rank tensor completion via local and nonlocal knowledge.
Inf. Sci., February, 2024

2023
Generalized nonconvex regularization for tensor RPCA and its applications in visual inpainting.
Appl. Intell., October, 2023

Guaranteed Tensor Recovery Fused Low-rankness and Smoothness.
IEEE Trans. Pattern Anal. Mach. Intell., September, 2023

Low-Tubal-Rank tensor recovery with multilayer subspace prior learning.
Pattern Recognit., August, 2023

Exact Decomposition of Joint Low Rankness and Local Smoothness Plus Sparse Matrices.
IEEE Trans. Pattern Anal. Mach. Intell., May, 2023

Tensor Robust Principal Component Analysis From Multilevel Quantized Observations.
IEEE Trans. Inf. Theory, 2023

Hyperspectral Image Denoising via Nonlocal Spectral Sparse Subspace Representation.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2023

Randomized sampling techniques based low-tubal-rank plus sparse tensor recovery.
Knowl. Based Syst., 2023

High-Order Tensor Recovery Coupling Multilayer Subspace Priori with Application in Video Restoration.
Proceedings of the 31st ACM International Conference on Multimedia, 2023

Tensor Compressive Sensing Fused Low-Rankness and Local-Smoothness.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Generalized Nonconvex Approach for Low-Tubal-Rank Tensor Recovery.
IEEE Trans. Neural Networks Learn. Syst., 2022

Large-Scale Affine Matrix Rank Minimization With a Novel Nonconvex Regularizer.
IEEE Trans. Neural Networks Learn. Syst., 2022

Low-Rank High-Order Tensor Completion With Applications in Visual Data.
IEEE Trans. Image Process., 2022

Robust Low-Rank Matrix Recovery Fusing Local-Smoothness.
IEEE Signal Process. Lett., 2022

A Novel Approach to Large-Scale Dynamically Weighted Directed Network Representation.
IEEE Trans. Pattern Anal. Mach. Intell., 2022

Robust Low-Tubal-Rank Tensor Recovery From Binary Measurements.
IEEE Trans. Pattern Anal. Mach. Intell., 2022

Robust High-Order Tensor Recovery Via Nonconvex Low-Rank Approximation.
Proceedings of the IEEE International Conference on Acoustics, 2022

2021
Low-Tubal-Rank Plus Sparse Tensor Recovery With Prior Subspace Information.
IEEE Trans. Pattern Anal. Mach. Intell., 2021

Performance guarantees of transformed Schatten-1 regularization for exact low-rank matrix recovery.
Int. J. Mach. Learn. Cybern., 2021

Denoising convolutional neural network inspired via multi-layer convolutional sparse coding.
J. Electronic Imaging, 2021

Robust low-rank tensor reconstruction using high-order t-SVD.
J. Electronic Imaging, 2021

Perturbation analysis of low-rank matrix stable recovery.
Int. J. Wavelets Multiresolution Inf. Process., 2021

An optimal condition of robust low-rank matrices recovery.
Int. J. Wirel. Mob. Comput., 2021

Tensor restricted isometry property analysis for a large class of random measurement ensembles.
Sci. China Inf. Sci., 2021

Non-Convex Sparse Deviation Modeling Via Generative Models.
Proceedings of the IEEE International Conference on Acoustics, 2021

2020
Uniqueness Guarantee of Solutions of Tensor Tubal-Rank Minimization Problem.
IEEE Signal Process. Lett., 2020

Accelerated inexact matrix completion algorithm via closed-form q-thresholding (q = 1/2, 2/3) operator.
Int. J. Mach. Learn. Cybern., 2020

RIP-based performance guarantee for low-tubal-rank tensor recovery.
J. Comput. Appl. Math., 2020

Robust principal component analysis with intra-block correlation.
Neurocomputing, 2020

CMCS-net: image compressed sensing with convolutional measurement via DCNN.
IET Image Process., 2020

The high-order block RIP for non-convex block-sparse compressed sensing.
CoRR, 2020

The perturbation analysis of nonconvex low-rank matrix robust recovery.
CoRR, 2020

An Optimal Condition of Robust Low-rank Matrices Recovery.
CoRR, 2020

An analysis of noise folding for low-rank matrix recovery.
CoRR, 2020

Estimating Structural Missing Values Via Low-Tubal-Rank Tensor Completion.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Low-Tubal-Rank Tensor Recovery From One-Bit Measurements.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019
A nonconvex penalty function with integral convolution approximation for compressed sensing.
Signal Process., 2019

Image denoising in impulsive noise via weighted Schatten p -norm regularization.
J. Electronic Imaging, 2019

Fast and efficient algorithm for matrix completion via closed-form 2/3-thresholding operator.
Neurocomputing, 2019

Sharp sufficient condition of block signal recovery via <i>l</i> <sub>2</sub>/<i>l</i> <sub>1</sub>-minimisation.
IET Signal Process., 2019

Block-sparse signal recovery based on truncated ℓ 1 minimisation in non-Gaussian noise.
IET Commun., 2019

Deterministic Analysis of Weighted BPDN With Partially Known Support Information.
CoRR, 2019

Coherence-Based Robust Analysis of Basis Pursuit De-Noising and Beyond.
IEEE Access, 2019

2018
基于子空间阈值追踪的矩阵修补算法 (Matrix Completion Algorithm Based on Subspace Thresholding Pursuit).
计算机科学, 2018

An inertial projection neural network for sparse signal reconstruction via l1-2 minimization.
Neurocomputing, 2018

Block-sparse signal recovery via ℓ 2 / ℓ 1 - 2 minimisation method.
IET Signal Process., 2018

Reconstruction analysis of block-sparse signal via truncated ℓ 2 / ℓ 1 -minimisation with redundant dictionaries.
IET Signal Process., 2018

Coherence-Based Performance Guarantee of Regularized 𝓁<sub>1</sub>-Norm Minimization and Beyond.
CoRR, 2018

Perturbations of Compressed Data Separation With Redundant Tight Frames.
IEEE Access, 2018

A Novel Thresholding Algorithm for Image Deblurring Beyond Nesterov's Rule.
IEEE Access, 2018

New Sufficient Conditions of Signal Recovery With Tight Frames via l<sub>1</sub>-Analysis Approach.
IEEE Access, 2018

2017
Robust Signal Recovery With Highly Coherent Measurement Matrices.
IEEE Signal Process. Lett., 2017

Non-convex block-sparse compressed sensing with redundant dictionaries.
IET Signal Process., 2017

A Fast and Robust TSVM for Pattern Classification.
CoRR, 2017

2016
A perturbation analysis of block-sparse compressed sensing via mixed ℓ2/ℓ1 minimization.
Int. J. Wavelets Multiresolution Inf. Process., 2016

Kernel canonical correlation analysis via gradient descent.
Neurocomputing, 2016

Perona-Malik Model with a New Diffusion Coefficient for Image Denoising.
Int. J. Image Graph., 2016

Block-sparse compressed sensing with partially known signal support via non-convex minimisation.
IET Signal Process., 2016

2015
Confirming robustness of fuzzy support vector machine via ξ-α bound.
Neurocomputing, 2015

A perturbation analysis of nonconvex block-sparse compressed sensing.
Commun. Nonlinear Sci. Numer. Simul., 2015

Coordinate Descent Fuzzy Twin Support Vector Machine for Classification.
Proceedings of the 14th IEEE International Conference on Machine Learning and Applications, 2015

2014
Restricted p-isometry properties of nonconvex block-sparse compressed sensing.
Signal Process., 2014

Active Contours Driven by Local Intensity and Local Gradient Fitting energies.
Int. J. Pattern Recognit. Artif. Intell., 2014

2013
On recovery of block-sparse signals via mixed l<sub>2</sub>/l<sub>q</sub> (0 < q ≤ 1) norm minimization.
EURASIP J. Adv. Signal Process., 2013

2012
Approximation of algebraic and trigonometric polynomials by feedforward neural networks.
Neural Comput. Appl., 2012

Estimation of Approximating Rate for Neural Network inLwp Spaces.
J. Appl. Math., 2012

Derivatives of Multivariate <i>Bernstein</i> Operators and Smoothness with <i>Jacobi</i> Weights.
J. Appl. Math., 2012

Constructive Estimation of Approximation for trigonometric Neural Networks.
Int. J. Wavelets Multiresolution Inf. Process., 2012

L2-loss twin support vector machine for classification.
Proceedings of the 5th International Conference on BioMedical Engineering and Informatics, 2012

2011
Neural networks and the best trigomometric approximation.
J. Syst. Sci. Complex., 2011

2010
New study on neural networks: the essential order of approximation.
Neural Networks, 2010

2009
Margin calibration in SVM class-imbalanced learning.
Neurocomputing, 2009

Estimation of Covering Number in Learning Theory.
Proceedings of the Fifth International Conference on Semantics, Knowledge and Grid, 2009

Generalization Performance of ERM Algorithm with Geometrically Ergodic Markov Chain Samples.
Proceedings of the Fifth International Conference on Natural Computation, 2009

How to Measure the Essential Approximation Capability of a FNN.
Proceedings of the Fifth International Conference on Natural Computation, 2009

2008
Imbalanced SVM Learning with Margin Compensation.
Proceedings of the Advances in Neural Networks, 2008

2007
Constructive Trigonometric Function Approximation of Neural Networks.
Proceedings of the Third International Conference on Semantics, 2007

2006
The essential order of approximation for nearly exponential type neural networks.
Sci. China Ser. F Inf. Sci., 2006

Approximation Bound of Mixture Networks in <i>L</i><sub><i>omega</i></sub><sup><i>p</i></sup> Spaces.
Proceedings of the Advances in Neural Networks - ISNN 2006, Third International Symposium on Neural Networks, Chengdu, China, May 28, 2006

2004
Approximation Bounds by Neural Networks in L<sup>p</sup><sub>omega</sub>.
Proceedings of the Advances in Neural Networks, 2004


  Loading...