Interpretable Multi-View Clustering Based on Anchor Graph Tensor Factorization

arXiv:2404.00883v1 Announce Type: new
Abstract: The clustering method based on the anchor graph has gained significant attention due to its exceptional clustering performance and ability to process large-scale data. One common approach is to learn bipartite graphs with K-connected components, helping avoid the need for post-processing. However, this method has strict parameter requirements and may not always get K-connected components. To address this issue, an alternative approach is to directly obtain the cluster label matrix by performing non-negative matrix factorization …

abstract anchor arxiv attention clustering components cs.lg data factorization graph graphs however learn performance post-processing process processing scale tensor type view