The k-means algorithm with cosine similarity, also known as the spherical k-means algorithm, is a popular method for clustering document collections. However, spherical k-means ca...
Abstract. Many applications of machine learning involve sparse highdimensional data, where the number of input features is (much) larger than the number of data samples, d n. Predi...
We consider the problem of uniform sampling of points on an algebraic variety. Specifically, we develop a randomized algorithm that, given a small set of multivariate polynomials ...
Abstract Parallel algorithms for the approximation of a multi-dimensional integral over an hyper-rectangular region are discussed. Algorithms based on quasi-Monte Carlo techniques ...