Dual-constrained Deep Semi-Supervised Coupled Factorization Network with Enriched Prior

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Abstract:

Nonnegative matrix factorization is usually powerful for learning the "shallow" parts-based representation, but it clearly fails to discover deep hierarchical information within both the basis and representation spaces. In this paper, we technically propose a new enriched prior based Dual-constrained Deep Semi-Supervised Coupled Factori...More

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