In multiview learning, it is essential to assign a reasonable weight to each view according to the view importance. Thus, for multiview clustering task, a wise and elegant method should achieve clustering multiview data while learning the view weights. In this paper, we propose to explore a ...
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Multiple kernel clustering with local kernel reconstruction and global heat diffusion 2024, Information Fusion Citation Excerpt : The MKC-NCKL approaches are characterized by the extraction of multiple graphs from candidate kernels and their integration into a consensus graph, eliminating the need for int...
IJCAI17: Self-Weighted Multiview Clustering with Multiple Graphs"Papercode TKDE2018: One-step multi-view spectral clusteringPapercode TKDE19: GMC: Graph-based Multi-view ClusteringPapercode ICDM2019: Consistency Meets Inconsistency: A Unified Graph Learning Framework for Multi-view ClusteringPapercode ...
These papers primarily consider unilayer binary undirected graphs which limits their application beyond this framework. As noted by Kivelä et al. [36], “most real and engineered systems include multiple subsystems and layers of connectivity, and developing a deep understanding of multilayer systems...
Graphs Each graph consists of a set of nodes connected to each other with a set of edges. In single-cell RNA sequencing, nodes are cells, and edges are determined according to cell–cell pairwise distances. Heuristic optimization A method for solving a problem that is designed to sacrifice ...
When clustering spots in diverse ST datasets, GraphST was better than competing methods at identifying biologically accurate structures in highly heterogeneous tissue samples. We also demonstrated GraphST’s ability at vertical and horizontal data integration with multiple tissue samples. GraphST detected ...
When clustering spots in diverse ST datasets, GraphST was better than competing methods at identifying biologically accurate structures in highly heterogeneous tissue samples. We also demonstrated GraphST’s ability at vertical and horizontal data integration with multiple tissue samples. GraphST detected ...
Types of neighbourhood graphs.aFully-connected graph;b\(\epsilon\)-neighbourhood graph;ck-neighbourhood graph for weighted graphs, all the edge weights inband b would not be replaced by 1 Full size image Fully connected graph [16,17]: Any data points with positive adjacency values can be conn...