Abstract. A very compact algorithm is presented for fundamental matrix computation from point correspondences over two images. The computation is based on the strict maximum likeli...
Nonnegative Matrix Factorization (NMF) approximates a given data matrix as a product of two low rank nonnegative matrices, usually by minimizing the L2 or the KL distance between ...
Given a large sparse graph, how can we find patterns and anomalies? Several important applications can be modeled as large sparse graphs, e.g., network traffic monitoring, resea...
We study the common problem of approximating a target matrix with a matrix of lower rank. We provide a simple and efficient (EM) algorithm for solving weighted low-rank approximat...
Multidocument extractive summarization relies on the concept of sentence centrality to identify the most important sentences in a document. Centrality is typically defined in term...