André van Hameren

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The thresholding of document scores has proved critical for the effectiveness of classification tasks. We review the most important approaches to thresholding, and introduce the<italic>score-distributional (S-D) threshold optimization</italic>method. The method is based on score distributions and is capable of optimizing any effectiveness measure defined in(More)
We consider one-loop tensor and scalar integrals, which occur in a massless quantum field theory and we report on the implementation into a numerical program of an algorithm for the automated computation of these one-loop integrals. The number of external legs of the loop integrals is not restricted. All calculations are done within dimensional(More)
We present an algorithm to generate any number of randommassless momenta in phase space, with a distribution that contains the kinematical pole structure that is typically found in multi-parton QCD-processes. As an application, we calculate the cross-section of some ee → partons processes, and compare SARGE’s performance with that of the uniform-phase space(More)
We present an aid for importance sampling in Monte Carlo integration, which is of the general-purpose type in the sense that it in principle deals with any quadratically integrable integrand on a unit hyper-cube of arbitrary dimension. In contrast to most existing systems of this type, it does not ask for the integrand as an input variable, but provides a(More)
We study the production of forward di-jets in proton-lead and proton-proton collisions at the Large Hadron Collider. Such configurations, with both jets produced in the forward direction, impose a dilute-dense asymmetry which allows to probe the gluon density of the lead or proton target at small longitudinal momentum fractions. Even though the jet momenta(More)
The concept of discrepancy plays an important rôle in the study of uniformity properties of point sets. For sets of random points, the discrepancy is a random variable. We apply techniques from quantum field theory to translate the problem of calculating the probability density of (quadratic) discrepancies into that of evaluating certain path integrals.(More)
For the Lego discrepancy with M bins, which is equivalent with a χ2-statistic with M bins, we present a procedure to calculate the moment generating function of the probability distribution perturbatively if M and N , the number of uniformly and randomly distributed data points, become large. Furthermore, we present a phase diagram for various limits of the(More)