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The effective rate for the variable-rate transmission is computed by maximizing (13) over ε.
Each year, equilibrium is computed by maximizing the global "net social payoff," while year-by-year changes are simulated by recursive programming.
A shared latent space is computed by maximizing the joint likelihood function of the audio and visual data sets, using Gaussian kernels.
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The unknown parameters of FDMM are computed by maximizing a posteriori (MAP) estimation.
Initial matrices are computed by maximizing the centered-kernel alignment (CKA) metric, measuring the affinity between projected samples and labels.
The maximum likelihood estimates (MLEs) of the parameters are computed by maximizing the objective function via the subroutine NLMIXED in SAS.
The maximum likelihood estimation of model parameters can be computed by maximizing (14) numerically.
Confidence intervals for reaction rates were computed by maximizing and minimizing the value of each reaction in turn subject to a slightly relaxed score.
Thus, the maximum likelihood estimate of the parameter vector can be computed by maximizing Eq. (A3) with respect to the parameters.
As argued by Gold et al. (1999), optimal performance for this task can be computed by maximizing the cross-correlation between the filtered, noise-masked stimulus and each of the templates (unfiltered action videos).
The transformations required to map this image to the structural scan for each individual and then from "structural space" to the Talairach template are computed by maximizing the correlation between the images at each stage.
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