Zheng Wang

According to our database, Zheng Wang authored at least 36 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Sparse Trace Ratio LDA for Supervised Feature Selection.

Zhengxin Li, Feiping Nie, Danyang Wu, Zheng Wang, Xuelong Li

IEEE Trans. Cybern., April, 2024

Outliers Robust Unsupervised Feature Selection for Structured Sparse Subspace.

Sisi Wang, Feiping Nie, Zheng Wang, Rong Wang, Xuelong Li

IEEE Trans. Knowl. Data Eng., March, 2024

Geometric-inspired graph-based Incomplete Multi-view Clustering.

Zequn Yang, Han Zhang, Yake Wei, Zheng Wang, Feiping Nie, Di Hu

Pattern Recognit., March, 2024

Worst-Case Discriminative Feature Learning via Max-Min Ratio Analysis.

Zheng Wang, Feiping Nie, Canyu Zhang, Rong Wang, Xuelong Li

IEEE Trans. Pattern Anal. Mach. Intell., January, 2024

2023

Local Embedding Learning via Landmark-Based Dynamic Connections.

Feiping Nie, Canyu Zhang, Zheng Wang, Rong Wang, Xuelong Li

IEEE Trans. Neural Networks Learn. Syst., November, 2023

Discrete Robust Principal Component Analysis via Binary Weights Self-Learning.

Feiping Nie, Sisi Wang, Zheng Wang, Rong Wang, Xuelong Li

IEEE Trans. Neural Networks Learn. Syst., November, 2023

Simultaneous local clustering and unsupervised feature selection via strong space constraint.

Zheng Wang, Qi Li, Haifeng Zhao, Feiping Nie

Pattern Recognit., October, 2023

Fast spectral clustering with self-adapted bipartite graph learning.

Xiaojun Yang, Mingjun Zhu, Yongda Cai, Zheng Wang, Feiping Nie

Inf. Sci., October, 2023

Sparse robust subspace learning via boolean weight.

Sisi Wang, Feiping Nie, Zheng Wang, Rong Wang, Xuelong Li

Inf. Fusion, August, 2023

Sparse and Flexible Projections for Unsupervised Feature Selection.

Rong Wang, Canyu Zhang, Jintang Bian, Zheng Wang, Feiping Nie, Xuelong Li

IEEE Trans. Knowl. Data Eng., June, 2023

Self-Supervised Learning for Heterogeneous Audiovisual Scene Analysis.

Di Hu, Zheng Wang, Feiping Nie, Rong Wang, Xuelong Li

IEEE Trans. Multim., 2023

Fuzzy C-Multiple-Means Clustering for Hyperspectral Image.

Xiaojun Yang, Mingjun Zhu, Bo Sun, Zheng Wang, Feiping Nie

IEEE Geosci. Remote. Sens. Lett., 2023

Max-Min Robust Principal Component Analysis.

Sisi Wang, Feiping Nie, Zheng Wang, Rong Wang, Xuelong Li

Neurocomputing, 2023

Unsupervised Feature Selection with self-Weighted and ℓ2,0-Norm Constraint.

Yongjin Yuan, Zheng Wang, Feiping Nie, Xuelong Li

Proceedings of the IEEE International Conference on Acoustics, 2023

2022

Adaptive Local Embedding Learning for Semi-Supervised Dimensionality Reduction.

Feiping Nie, Zheng Wang, Rong Wang, Xuelong Li

IEEE Trans. Knowl. Data Eng., 2022

Subspace Sparse Discriminative Feature Selection.

Feiping Nie, Zheng Wang, Lai Tian, Rong Wang, Xuelong Li

IEEE Trans. Cybern., 2022

Self-weighted learning framework for adaptive locality discriminant analysis.

Wei Chang, Feiping Nie, Zheng Wang, Rong Wang, Xuelong Li

Pattern Recognit., 2022

Capped ℓp-norm linear discriminant analysis for robust projections learning.

Zheng Wang, Haojie Hu, Rong Wang, Qianrong Zhang, Feiping Nie, Xuelong Li

Neurocomputing, 2022

A Survey on Legal Judgment Prediction: Datasets, Metrics, Models and Challenges.

Junyun Cui, Xiaoyu Shen, Feiping Nie, Zheng Wang, Jinglong Wang, Yulong Chen

CoRR, 2022

Joint Adaptive Graph Learning and Discriminative Analysis for Unsupervised Feature Selection.

Haifeng Zhao, Qi Li, Zheng Wang, Feiping Nie

Cogn. Comput., 2022

2021

Joint nonlinear feature selection and continuous values regression network.

Zheng Wang, Feiping Nie, Canyu Zhang, Rong Wang, Xuelong Li

Pattern Recognit. Lett., 2021

Local structured feature learning with dynamic maximum entropy graph.

Zheng Wang, Feiping Nie, Rong Wang, Hui Yang, Xuelong Li

Pattern Recognit., 2021

Towards Robust Discriminative Projections Learning via Non-Greedy $\ell _{2, 1}$ℓ2, 1-Norm MinMax.

Feiping Nie, Zheng Wang, Rong Wang, Zhen Wang, Xuelong Li

IEEE Trans. Pattern Anal. Mach. Intell., 2021

Fast local representation learning via adaptive anchor graph for image retrieval.

Canyu Zhang, Feiping Nie, Zheng Wang, Rong Wang, Xuelong Li

Inf. Sci., 2021

Fast Local Representation Learning with Adaptive Anchor Graph.

Canyu Zhang, Feiping Nie, Zheng Wang, Rong Wang, Xuelong Li

Proceedings of the IEEE International Conference on Acoustics, 2021

2020

Adaptive Local Linear Discriminant Analysis.

Feiping Nie, Zheng Wang, Rong Wang, Zhen Wang, Xuelong Li

ACM Trans. Knowl. Discov. Data, 2020

Submanifold-Preserving Discriminant Analysis With an Auto-Optimized Graph.

Feiping Nie, Zheng Wang, Rong Wang, Xuelong Li

IEEE Trans. Cybern., 2020

Capped ℓ_p-Norm LDA for Outliers Robust Dimension Reduction.

Zheng Wang, Feiping Nie, Canyu Zhang, Rong Wang, Xuelong Li

IEEE Signal Process. Lett., 2020

Multiclass discriminant analysis via adaptive weighted scheme.

Haifeng Zhao, Bowen Zhang, Zheng Wang, Feiping Nie

Neurocomputing, 2020

Curriculum Audiovisual Learning.

Di Hu, Zheng Wang, Haoyi Xiong, Dong Wang, Feiping Nie, Dejing Dou

CoRR, 2020

Discriminative Feature Selection via A Structured Sparse Subspace Learning Module.

Zheng Wang, Feiping Nie, Lai Tian, Rong Wang, Xuelong Li

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

2019

A New Formulation of Linear Discriminant Analysis for Robust Dimensionality Reduction.

Haifeng Zhao, Zheng Wang, Feiping Nie

IEEE Trans. Knowl. Data Eng., 2019

Robust Linear Discriminant Analysis Using Ratio Minimization of L1, 2-Norms.

Feiping Nie, Hua Wang, Zheng Wang, Heng Huang

CoRR, 2019

2018

Multiclass Classification and Feature Selection Based on Least Squares Regression with Large Margin.

Haifeng Zhao, Siqi Wang, Zheng Wang

Neural Comput., 2018

Adaptive Neighborhood MinMax Projections.

Haifeng Zhao, Zheng Wang, Feiping Nie

Neurocomputing, 2018

2016

Orthogonal least squares regression for feature extraction.

Haifeng Zhao, Zheng Wang, Feiping Nie

Neurocomputing, 2016