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...
Background: Modern high throughput experimental techniques such as DNA microarrays often result in large lists of genes. Computational biology tools such as clustering are then us...
Alain B. Tchagang, Alexander Gawronski, Hugo B&eac...
Background: Pathways provide topical descriptions of cellular circuitry. Comparing analogous pathways reveals intricate insights into individual functional differences among speci...
Abstract. A new constrained model is discussed as a way of incorporating efficiently a priori expert knowledge into a clustering problem of a given individual set. The first innova...
—A new formulation for multiway spectral clustering is proposed. This method corresponds to a weighted kernel principal component analysis (PCA) approach based on primal-dual lea...