Ming Yang

Orcid: 0000-0003-1810-1566

Affiliations:
  • Westfield State University, Department of Computer and Information Science, Westfield, MA, USA
  • Southern Illinois University, Department of Computer Science, Carbondale, IL, USA
  • Texas A&M University, College Station, TX, USA (PhD 2012)


According to our database1, Ming Yang authored at least 32 papers between 2016 and 2024.

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

Timeline

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Bibliography

2024
Self-adaptive SURF for image-to-video matching.
Signal Image Video Process., February, 2024

Efficient Anchor Graph Factorization for Multi-View Clustering.
IEEE Trans. Multim., 2024

Unsupervised Discriminative Feature Selection via Contrastive Graph Learning.
IEEE Trans. Image Process., 2024

Efficient Multi-View -Means for Image Clustering.
IEEE Trans. Image Process., 2024

2023
Sparse discriminant PCA based on contrastive learning and class-specificity distribution.
Neural Networks, October, 2023

Contrastive self-representation learning for data clustering.
Neural Networks, October, 2023

Active learning based on similarity level histogram and adaptive-scale sampling for very high resolution image classification.
Neural Networks, October, 2023

Low-rank discrete multi-view spectral clustering.
Neural Networks, September, 2023

Sliced Sparse Gradient Induced Multi-View Subspace Clustering via Tensorial Arctangent Rank Minimization.
IEEE Trans. Knowl. Data Eng., July, 2023

Joint feature selection and optimal bipartite graph learning for subspace clustering.
Neural Networks, July, 2023

Self-Consistent Contrastive Attributed Graph Clustering With Pseudo-Label Prompt.
IEEE Trans. Multim., 2023

Self-Weighted Anchor Graph Learning for Multi-View Clustering.
IEEE Trans. Multim., 2023

Hyper-Laplacian Regularized Multi-View Clustering with Exclusive L21 Regularization and Tensor Log-Determinant Minimization Approach.
ACM Trans. Intell. Syst. Technol., 2023

Graph Embedding Contrastive Multi-Modal Representation Learning for Clustering.
IEEE Trans. Image Process., 2023

Adaptive multi-granularity sparse subspace clustering.
Inf. Sci., 2023

2022
3-D Array Image Data Completion by Tensor Decomposition and Nonconvex Regularization Approach.
IEEE Trans. Signal Process., 2022

Multiview Spectral Clustering With Bipartite Graph.
IEEE Trans. Image Process., 2022

View-Consistency Learning for Incomplete Multiview Clustering.
IEEE Trans. Image Process., 2022

Nonconvex 3D array image data recovery and pattern recognition under tensor framework.
Pattern Recognit., 2022

Multi-view graph embedding clustering network: Joint self-supervision and block diagonal representation.
Neural Networks, 2022

Cross-modal distribution alignment embedding network for generalized zero-shot learning.
Neural Networks, 2022

2021
Self-supervised Contrastive Attributed Graph Clustering.
CoRR, 2021

Robust Multiview Subspace Clustering of Images via Tighter Rank Approximation.
IEEE Access, 2021

Enhancing Effectiveness of Teaching Evaluation using Blockchain and Regulated Token Economy.
Proceedings of the 16th International Conference on Computer Science & Education, 2021

2020
Multiview Clustering of Images with Tensor Rank Minimization via Nonconvex Approach.
SIAM J. Imaging Sci., 2020

A Mobile Robot Visual SLAM System With Enhanced Semantics Segmentation.
IEEE Access, 2020

On the Modeling and Predication of Teaching Effectiveness with Machine Learning.
Proceedings of the 15th International Conference on Computer Science & Education, 2020

2018
Image Denoising via Improved Dictionary Learning with Global Structure and Local Similarity Preservations.
Symmetry, 2018

2017
Exploiting Nonlinear Relationships for Top-N Recommender Systems.
Proceedings of the IEEE International Conference on Big Knowledge, 2017

2016
Feature Selection Embedded Subspace Clustering.
IEEE Signal Process. Lett., 2016

RAP: Scalable RPCA for Low-rank Matrix Recovery.
Proceedings of the 25th ACM International Conference on Information and Knowledge Management, 2016

Top-N Recommendation on Graphs.
Proceedings of the 25th ACM International Conference on Information and Knowledge Management, 2016


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