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Optimisation algorithms work by trying to minimise a function of the parameters.
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The objective is to minimise a function describing die underfill and excessive material waste.
In this paper therefore, we modify a multilevel algorithm in order to minimise a cost function based on a model of the communications network.
A risk-based approach has been incorporated in the procedure in order to minimise an objective function that involves the mitigation actions of risks.
Finally, a key-frame refinement method is employed to minimise an error function which incorporates visual saliency information.
In order to minimise the function, we consider the problem of layer evolution and disparity estimation separately and then show how the problem is iteratively solved in Section 3.2.4.
We shall note that better models have a lower perplexity, and we can decide either to minimise the criterion function or to use the negative value of the perplexity as a criterion function T and maximize it.
An iterative search is carried out, which attempts to minimise the discrepancy function (F), a measure of the difference between S and Σ.
Internal model parameters are then varied by a numerical optimisation algorithm [24] in order to minimise this cost function.
The values of those estimated parameters were then changed to minimise the objective function value.
3D6 has strong target binding and a high risk of causing vascular side effects and inflammation, therefore, to minimise toxicity reduction of its effector function will likely be beneficial.
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