Orthogonal NMF through Subspace Exploration

NeurIPS 2015 Megasthenis AsterisDimitris PapailiopoulosAlexandros G. Dimakis

Orthogonal Nonnegative Matrix Factorization {(ONMF)} aims to approximate a nonnegative matrix as the product of two $k$-dimensional nonnegative factors, one of which has orthonormal columns. It yields potentially useful data representations as superposition of disjoint parts, while it has been shown to work well for clustering tasks where traditional methods underperform... (read more)

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