21 citations · 21 across the 1 of their papers we have counts for
9 papers
Interpretable Clustering: A Survey
Lianyu Hu, Mudi Jiang, Junjie Dong +2
In recent years, much of the research on clustering algorithms has primarily focused on enhancing their accuracy and efficiency, frequently at the expense of interpretability. Howe…
Clusterability-Based Assessment of Potentially Noisy Views for Multi-View Clustering
Mudi Jiang, Jiahui Zhou, Xinying Liu +2
In multi-view clustering, the quality of different views may vary substantially, and low-quality or degraded views can impair overall clustering performance. However, existing stud…
Biological Sequence Clustering: A Survey
Simeng Zhang, Xinying Liu, Jun Lou +3
The rapid development of high-throughput sequencing technologies has led to an explosive increase in biological sequence data, making sequence clustering a fundamental task in larg…
Interpretable Fair Clustering
Mudi Jiang, Jiahui Zhou, Xinying Liu +2
Fair clustering has gained increasing attention in recent years, especially in applications involving socially sensitive attributes. However, existing fair clustering methods often…
Adversarial Fair Multi-View Clustering
Mudi Jiang, Jiahui Zhou, Lianyu Hu +3
Cluster analysis is a fundamental problem in data mining and machine learning. In recent years, multi-view clustering has attracted increasing attention due to its ability to integ…
Two-cluster test
Xinying Liu, Lianyu Hu, Mudi Jiang +3
Cluster analysis is a fundamental research issue in statistics and machine learning. In many modern clustering methods, we need to determine whether two subsets of samples come fro…