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The advantage of minimizing cross entropy over minimizing variance is that the former yields biasing parameters with a closed-form solution for (2) where the latter does not.
The dwSSA computes low variance biasing parameters by minimizing cross entropy using a modified version of Rubinstein's multilevel cross-entropy method [ 17, 18].
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This minimization is usually carried out by minimizing the cross entropy using conjugate gradients.
The minimization in this paper is carried out by minimizing the cross entropy using conjugate gradients [22].
Recently, an adaptive importance sampling method was proposed to find a near-optimal importance sampling density by minimizing Kullback Leibler cross entropy, i.e. a measure of the difference between the absolute best sampling density and the one being used for the importance sampling.
The classical backpropagation is adopted to minimize the cross entropy error between outputs and targets.
The conjugate gradient algorithm was used to adjust the relative weightings of the units to minimize the cross entropy error for each training case [37].
The matrix is decomposed into and matrices in order to minimize the cross entropy (KL divergence) between the matrix and empirical distribution.
The neural mechanisms for minimizing cross-modal distraction.
Sales managers vigilantly protect turf, minimizing cross-department teamwork.
This approach effectively minimized cross pollination.
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