DeepAI AI Chat
Log In Sign Up

Multi-View Multiple Clusterings using Deep Matrix Factorization

by   Shaowei Wei, et al.
King Abdullah University of Science and Technology
George Mason University
Southwest University

Multi-view clustering aims at integrating complementary information from multiple heterogeneous views to improve clustering results. Existing multi-view clustering solutions can only output a single clustering of the data. Due to their multiplicity, multi-view data, can have different groupings that are reasonable and interesting from different perspectives. However, how to find multiple, meaningful, and diverse clustering results from multi-view data is still a rarely studied and challenging topic in multi-view clustering and multiple clusterings. In this paper, we introduce a deep matrix factorization based solution (DMClusts) to discover multiple clusterings. DMClusts gradually factorizes multi-view data matrices into representational subspaces layer-by-layer and generates one clustering in each layer. To enforce the diversity between generated clusterings, it minimizes a new redundancy quantification term derived from the proximity between samples in these subspaces. We further introduce an iterative optimization procedure to simultaneously seek multiple clusterings with quality and diversity. Experimental results on benchmark datasets confirm that DMClusts outperforms state-of-the-art multiple clustering solutions.


page 1

page 2

page 3

page 4


Deep Incomplete Multi-View Multiple Clusterings

Multi-view clustering aims at exploiting information from multiple heter...

Multi-View Multiple Clustering

Multiple clustering aims at exploring alternative clusterings to organiz...

Multi-view Clustering via Deep Matrix Factorization and Partition Alignment

Multi-view clustering (MVC) has been extensively studied to collect mult...

Latent Simplex Position Model: High Dimensional Multi-view Clustering with Uncertainty Quantification

High dimensional data often contain multiple facets, and several cluster...

Multi-way Spectral Clustering of Augmented Multi-view Data through Deep Collective Matrix Tri-factorization

We present the first deep learning based architecture for collective mat...

Multiple Independent Subspace Clusterings

Multiple clustering aims at discovering diverse ways of organizing data ...

Integrative Clustering of Multi-View Data by Nonnegative Matrix Factorization

Learning multi-view data is an emerging problem in machine learning rese...