Weixuan Liang
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View article: Generalization Performance of Ensemble Clustering: From Theory to Algorithm
Generalization Performance of Ensemble Clustering: From Theory to Algorithm Open
Ensemble clustering has demonstrated great success in practice; however, its theoretical foundations remain underexplored. This paper examines the generalization performance of ensemble clustering, focusing on generalization error, excess …
View article: Incremental Nyström-based Multiple Kernel Clustering
Incremental Nyström-based Multiple Kernel Clustering Open
Existing Multiple Kernel Clustering (MKC) algorithms commonly utilize the Nyström method to handle large-scale datasets. However, most of them employ uniform sampling for kernel matrix approximation, hence failing to accurately capture the…
View article: Contents
Contents Open
Turning up our understanding of liver cancer by a notch
View article: Scalable Incomplete Multi-View Clustering with Structure Alignment
Scalable Incomplete Multi-View Clustering with Structure Alignment Open
The success of existing multi-view clustering (MVC) relies on the assumption\nthat all views are complete. However, samples are usually partially available\ndue to data corruption or sensor malfunction, which raises the research of\nincomp…
View article: Unpaired Multi-View Graph Clustering with Cross-View Structure Matching
Unpaired Multi-View Graph Clustering with Cross-View Structure Matching Open
Multi-view clustering (MVC), which effectively fuses information from multiple views for better performance, has received increasing attention. Most existing MVC methods assume that multi-view data are fully paired, which means that the ma…
View article: Auto-Weighted Multi-View Clustering for Large-Scale Data
Auto-Weighted Multi-View Clustering for Large-Scale Data Open
Multi-view clustering has gained broad attention owing to its capacity to exploit complementary information across multiple data views. Although existing methods demonstrate delightful clustering performance, most of them are of high time …
View article: Fast Continual Multi-View Clustering with Incomplete Views
Fast Continual Multi-View Clustering with Incomplete Views Open
Multi-view clustering (MVC) has gained broad attention owing to its capacity to exploit consistent and complementary information across views. This paper focuses on a challenging issue in MVC called the incomplete continual data problem (I…
View article: Auto-weighted Multi-view Clustering for Large-scale Data
Auto-weighted Multi-view Clustering for Large-scale Data Open
Multi-view clustering has gained broad attention owing to its capacity to exploit complementary information across multiple data views. Although existing methods demonstrate delightful clustering performance, most of them are of high time …
View article: Robust Graph-Based Multi-View Clustering
Robust Graph-Based Multi-View Clustering Open
Graph-based multi-view clustering (G-MVC) constructs a graphical representation of each view and then fuses them to a unified graph for clustering. Though demonstrating promising clustering performance in various applications, we observe t…
View article: Trade-off Between Efficiency and Effectiveness: A Late Fusion Multi-view Clustering Algorithm
Trade-off Between Efficiency and Effectiveness: A Late Fusion Multi-view Clustering Algorithm Open
Late fusion multi-view clustering (LFMVC) algorithms aim to integrate the base partition of each single view into a consensus partition. Base partitions can be obtained by performing kernel k-means clustering on all views. This type of met…
View article: Multi-View Clustering With Learned Bipartite Graph
Multi-View Clustering With Learned Bipartite Graph Open
In this paper, we propose a late fusion multi-view clustering via a learned bipartite graph (MVC-LBG). Firstly, we obtain the base partition from each single view. Then, a consensus bipartite graph is constructed by these base partitions f…
View article: Multi-View Spectral Clustering with High-Order Optimal Neighborhood Laplacian Matrix
Multi-View Spectral Clustering with High-Order Optimal Neighborhood Laplacian Matrix Open
Multi-view spectral clustering can effectively reveal the intrinsic cluster structure among data by performing clustering on the learned optimal embedding across views. Though demonstrating promising performance in various applications, mo…