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

Code

• bitbucket.org/cdal/dcmtf_generic
  OfficialIn paperpytorch★ 0

Abstract

We present the first deep learning based architecture for collective matrix tri-factorization (DCMTF) of arbitrary collections of matrices, also known as augmented multi-view data. DCMTF can be used for multi-way spectral clustering of heterogeneous collections of relational data matrices to discover latent clusters in each input matrix, across both dimensions, as well as the strengths of association across clusters. The source code for DCMTF is available on our public repository: https://bitbucket.org/cdal/dcmtf_generic

Tasks

Reproductions