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Laurent Carraro

  1. Additive Covariance Kernels for High-Dimensional Gaussian Process Modeling.

    Втр, 11/29/2011 - 15:01 — SomNambul
    Authors: Laurent Carraro, David Ginsbourger, Nicolas Durrande, Olivier Roustant
    Subjects: Machine Learning
    Abstract

    Gaussian process models -also called Kriging models- are often used as
    mathematical approximations of expensive experiments. However, the number of
    observation required for building an emulator becomes unrealistic when using
    classical covariance kernels when the dimension of input increases. In oder to
    get round the curse of dimensionality, a popular approach is to consider
    simplified models such as additive models.

  2. On Azema-Yor processes, their optimal properties and the Bachelier-Drawdown equation.

    Пнд, 08/31/2009 - 17:16 — SomNambul
    Authors: Laurent Carraro, Nicole El Karoui, Jan Obloj
    Subjects: Probability
    Abstract

    We study the class of Azema-Yor processes defined from a general
    semimartingale with a continuous running supremum process. We show that they
    arise as unique strong solutions of the Bachelier stochastic differential
    equation which we prove is equivalent to the Drawdown equation. Solutions of
    the latter have the drawdown property: they always stay above a given function
    of their past supremum. We then show that any process which satisfies the
    drawdown property is in fact an Azema-Yor process.

Math-arch

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