Ming Li
Affiliations:- Jiangsu Ocean University, Department of Computer Science and Technology, China
- University of Shanghai for Science and Technology, Department of Optical-Electrical and Computer Engineering, , China (PhD 2023)
According to our database1,
Ming Li
authored at least 15 papers
between 2019 and 2024.
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Bibliography
2024
Switching Triple-Weight-SMOTE in Empirical Feature Space for Imbalanced and Incomplete Data.
IEEE Trans Autom. Sci. Eng., April, 2024
Biased collective latent factorization of tensors with transfer learning for dynamic QoS data predicting.
Digit. Signal Process., 2024
2023
A Biologically-Inspired Sparse Self-Representation Approach for Projected Fuzzy Double C-Means Clustering.
Cogn. Comput., November, 2023
An Improved Non-Negative Latent Factor Model for Missing Data Estimation via Extragradient-Based Alternating Direction Method.
IEEE Trans. Neural Networks Learn. Syst., September, 2023
A general robust low-rank multinomial logistic regression for corrupted matrix data classification.
Appl. Intell., August, 2023
Switching synthesizing-incorporated and cluster-based synthetic oversampling for imbalanced binary classification.
Eng. Appl. Artif. Intell., 2023
2022
IEEE Trans. Syst. Man Cybern. Syst., 2022
Nonnegative Latent Factor Analysis-Incorporated and Feature-Weighted Fuzzy Double $c$-Means Clustering for Incomplete Data.
IEEE Trans. Fuzzy Syst., 2022
An enhanced matrix completion method based on non-negative latent factors for recommendation system.
Expert Syst. Appl., 2022
Appl. Intell., 2022
Latent Factor Learning Under Multiple Rating Patterns for Undirected, Large-Scaled and Sparse Networks.
Proceedings of the IEEE International Conference on Industrial Technology, 2022
2021
Nonnegative Latent Factor-Incorporated Fuzzy Double c-Means Clustering for Incomplete Data.
Proceedings of the IEEE International Conference on Smart Data Services, 2021
Fuzzy C-Means Clustering With Neighbor Information Constraint Using Sparse Self-Representation.
Proceedings of the IEEE International Conference on Networking, Sensing and Control, 2021
2020
Improved Symmetric and Nonnegative Matrix Factorization Models for Undirected, Sparse and Large-Scaled Networks: A Triple Factorization-Based Approach.
IEEE Trans. Ind. Informatics, 2020
2019
Triple Factorization-Like Symmetric and Nonnegative Latent Factor Models for Undirected, Sparse and Large-Scaled Networks.
Proceedings of the 2019 IEEE International Conference on Systems, Man and Cybernetics, 2019