Mining discrete patterns in binary data is important for subsampling, compression, and clustering. We consider rankone binary matrix approximations that identify the dominant patt...
We study the complexity of approximating the smallest eigenvalue of −∆ + q with Dirichlet boundary conditions on the d-dimensional unit cube. Here ∆ is the Laplacian, and th...
Abstract. This paper proposes the Sequential Coordinate-Wise Algorithm (SCWA) to Discriminant Nonnegative Matrix Factorization (DNMF) for improving face recognition. DNMF incorpora...
In most IR clustering problems, we directly cluster the documents, working in the document space, using cosine similarity between documents as the similarity measure. In many real...
Subspace clustering and feature extraction are two of the most commonly used unsupervised learning techniques in computer vision and pattern recognition. State-of-theart technique...
Risheng Liu, Zhouchen Lin, Fernando De la Torre, Z...