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Based on the measures presented above, the problem is the search for an order that minimizes the objectives A and O.
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The WLS estimator minimizes the objective function by satisfying the first-order optimality conditions.
Recall that when, the solution is the input sample that minimizes the objective function.
The solution for B ~ is not unique, and the one which minimizes the objective function should be chosen.
There are many simple algorithms like gradient descent which estimate such a baseline that minimizes the objective function.
The variable will take on the value 1 if the operator is part of the query plan which minimizes the objective of the BIP and 0 otherwise.
An immunity genetic algorithm is then devised to determine the best IGA parameter sequence, which minimizes the objective function.
The dominating term is the cost of selecting the input sample that minimizes the objective function, that is, the cost of evaluating the objective function times.
The LSE algorithm minimizes the objective function f(x) = (f1 x))2+(f2(x))2+ ⋯ +(f N (x 2, which is the sum of the OFDM sub-carriers amplitudesh.
The goal is to determine the set of parameters which minimizes the objective function, i.e., the difference between experimental and simulated results.
If we have found a point which minimizes the objective function over its neighborhood, then the local search stops and the point obtained is called a local minimizer.
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