Auto-weighted multi-view co-clustering via fast matrix factorization

Volume: 102, Pages: 107207 - 107207
Published: Jun 1, 2020
Abstract
Multi-view clustering is a hot research topic in machine learning and pattern recognition, however, it remains high computational complexity when clustering multi-view data sets. Although a number of approaches have been proposed to accelerate the computational efficiency, most of them do not consider the data duality between features and samples. In this paper, we propose a novel co-clustering approach termed as Fast Multi-view Bilateral...
Paper Details
Title
Auto-weighted multi-view co-clustering via fast matrix factorization
Published Date
Jun 1, 2020
Volume
102
Pages
107207 - 107207
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