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Jeffrey S. Morris

  1. Automated analysis of quantitative image data using isomorphic functional mixed models, with application to proteomics data.

    Пнд, 08/22/2011 - 15:01 — SomNambul
    Authors: Jeffrey S. Morris, Veerabhadran Baladandayuthapani, Richard C. Herrick, Pietro Sanna, Howard Gutstein
    Subjects: Applications
    Abstract

    Image data are increasingly encountered and are of growing importance in many
    areas of science. Much of these data are quantitative image data, which are
    characterized by intensities that represent some measurement of interest in the
    scanned images. The data typically consist of multiple images on the same
    domain and the goal of the research is to combine the quantitative information
    across images to make inference about populations or interventions.

  2. Online Variational Bayes Inference for High-Dimensional Correlated Data.

    Пт, 08/05/2011 - 15:01 — SomNambul
    Authors: David B. Dunson, Sylvie Tchumtchoua, Jeffrey S. Morris
    Subjects: Computation
    Abstract

    High-dimensional data with hundreds of thousands of observations are becoming
    commonplace in many disciplines. The analysis of such data poses many
    computational challenges, especially when the observations are correlated over
    time and/or across space. In this paper we propose flexible hierarchical
    regression models for analyzing such data that accommodate serial and/or
    spatial correlation. We address the computational challenges involved in
    fitting these models by adopting an approximate inference framework.

Math-arch

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