We have developed a machine learning toolbox, called SHOGUN, which is designed for unified large-scale learning for a broad range of feature types and learning settings. It offers...
In this paper, we develop a novel online algorithm based on the Sequential Monte Carlo (SMC) samplers framework for posterior inference in Dirichlet Process Mixtures (DPM) (DelMor...
We study the forward and backward substitution phases of a sparse multifrontal factorization. These phases are often neglected in papers on sparse direct factorization but, in man...
Patrick Amestoy, Iain S. Duff, Abdou Guermouche, T...
This paper is concerned with classifying high dimensional data into one of two categories. In various settings, such as when dealing with fMRI and microarray data, the number of v...
A class of binary decision-making tasks called the two-alternative forced-choice task has been used extensively in psychology and behavioral economics experiments to investigate h...
Ming Cao, Andrew Reed Stewart, Naomi Ehrich Leonar...