Dexian Wang

Orcid: 0000-0002-7700-1023

Affiliations:

Chengdu University of Traditional Chinese Medicine (CDUTCM), Chengdu, China
Southwest Jiaotong University, Chengdu, China

According to our database¹, Dexian Wang authored at least 24 papers between 2020 and 2025.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of three.

Timeline

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In proceedings

Article

PhD thesis

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Other

Bibliography

2025

FedMDKGE: Multi-granularity Dynamic Knowledge Graph Embedding in Federated Learning.

[BibT_eX]

[DOI]

Int. J. Comput. Intell. Syst., December, 2025

ODMGIS: An Outlier Detection Method Based on Multigranularity Information Sets.

[BibT_eX]

[DOI]

IEEE Trans. Fuzzy Syst., July, 2025

NDRIDC: NMF-based deep representation algorithm for incomplete data clustering.

[BibT_eX]

[DOI]

Knowl. Based Syst., 2025

Information fusion and feature selection for multi-source data utilizing Dempster-Shafer evidence theory and K-nearest neighbors.

[BibT_eX]

[DOI]

Inf. Sci., 2025

I2QD: Unsupervised feature selection via information quality, quantity, and difference degree.

[BibT_eX]

[DOI]

Inf. Process. Manag., 2025

Central-peripheral nervous system activation in exoskeleton modes: A Granger causality analysis via EEG-EMG fusion.

[BibT_eX]

[DOI]

Expert Syst. Appl., 2025

2024

DNSRF: Deep Network-based Semi-NMF Representation Framework.

[BibT_eX]

[DOI]

ACM Trans. Intell. Syst. Technol., October, 2024

An autoencoder-like deep NMF representation learning algorithm for clustering.

[BibT_eX]

[DOI]

Knowl. Based Syst., 2024

A multi-scale information fusion-based multiple correlations for unsupervised attribute selection.

[BibT_eX]

[DOI]

Inf. Fusion, 2024

Multimodal federated learning: Concept, methods, applications and future directions.

[BibT_eX]

[DOI]

Inf. Fusion, 2024

A Dynamic Unsupervised Feature Selection Method Based on Information Sets and Fuzzy Rough Sets.

[BibT_eX]

[DOI]

Proceedings of the Rough Sets - International Joint Conference, 2024

2023

Fast attribute reduction via inconsistent equivalence classes for large-scale data.

[BibT_eX]

[DOI]

Int. J. Approx. Reason., December, 2023

A multi-view clustering algorithm based on deep semi-NMF.

[BibT_eX]

[DOI]

Inf. Fusion, November, 2023

A Possibilistic Information Fusion-Based Unsupervised Feature Selection Method Using Information Quality Measures.

[BibT_eX]

[DOI]

IEEE Trans. Fuzzy Syst., September, 2023

FedCKE: Cross-Domain Knowledge Graph Embedding in Federated Learning.

[BibT_eX]

[DOI]

IEEE Trans. Big Data, June, 2023

A multi-source information fusion model for outlier detection.

[BibT_eX]

[DOI]

Inf. Fusion, May, 2023

Multi-view clustering guided by unconstrained non-negative matrix factorization.

[BibT_eX]

[DOI]

Knowl. Based Syst., April, 2023

A Generalized Deep Learning Algorithm Based on NMF for Multi-View Clustering.

[BibT_eX]

[DOI]

IEEE Trans. Big Data, February, 2023

A Generalized Deep Learning Clustering Algorithm Based on Non-Negative Matrix Factorization.

[BibT_eX]

[DOI]

ACM Trans. Knowl. Discov. Data, 2023

Graph Regularized Sparse Non-Negative Matrix Factorization for Clustering.

[BibT_eX]

[DOI]

IEEE Trans. Comput. Soc. Syst., 2023

2022

Dual graph-regularized sparse concept factorization for clustering.

[BibT_eX]

[DOI]

Inf. Sci., 2022

Fairness and accuracy in horizontal federated learning.

[BibT_eX]

[DOI]

Inf. Sci., 2022

2021

Multi-source information fusion based on rough set theory: A review.

[BibT_eX]

[DOI]

Inf. Fusion, 2021

2020

Fairness and Accuracy in Federated Learning.

[BibT_eX]

[DOI]

CoRR, 2020

Dexian Wang

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