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arXiv · 1908.09419

Deep Closed-Form Subspace Clustering

Junghoon Seo·Jamyoung Koo·Taegyun Jeon
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Abstract

We propose Deep Closed-Form Subspace Clustering (DCFSC), a new embarrassingly simple model for subspace clustering with learning non-linear mapping. Compared with the previous deep subspace clustering (DSC) techniques, our DCFSC does not have any parameters at all for the self-expressive layer. Instead, DCFSC utilizes the implicit data-driven self-expressive layer derived from closed-form shallow auto-encoder. Moreover, DCFSC also has no complicated optimization scheme, unlike the other subspace clustering methods. With its extreme simplicity, DCFSC has significant memory-related benefits over the existing DSC method, especially on the large dataset. Several experiments showed that our DCFSC model had enough potential to be a new reference model for subspace clustering on large-scale high-dimensional dataset.

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Junghoon Seo, Jamyoung Koo, Taegyun Jeon. 2019-08-26. Deep Closed-Form Subspace Clustering. https://arxiv.org/abs/1908.09419

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