incomplete solution to a difficult problem and then iteratively looks for the best way to improve the solution. The process is repeated until some stopping condition is reached.Figure 2illustrates the important ideas of the maximum clique problem and shows you where I’m headed in this...
The main processing loop will terminate when the maximum number of iterations is reached or if a best solution with the target clique size is found. I use the cliqueChanged variable to control the branching logic between adding and dropping nodes, as you’ll see. The logic to add an allowed...
The maximization step is achieved by updating model parameters such that they are greater or equal to the initial model and then repeated until convergence is reached [25]. From a test speech signal (unknown speaker), features are extracted that form the inputs to the speaker models (i.e.,...
the oldest start becomes less and less important until finally a point in time is reached where the start is not factored into the calculation of the maximum number of starts per unit of time. A moving time window is provided which uses as its base in each case the last oldest non timed...
For all PSMIX runs, we set the stopping criterion to be that the parameter difference <10-6 between consecutive iterations, or 10,000 steps, whichever was reached first. For the same Pima-Surui data with 100 markers, each run of PSMIX needed about 6 seconds. To evaluate the accuracy of...
Unless conditional termination requirements are met, such as a target network score reached or a computational budget expended, the Bayesian Optimisation (BO) method is used to select the next candidate which is then evaluated with the objective function. Fig. 1 illustrates that the cycle of ...
The selection of individuals with similar characteristics from a given population have always been a matter of interest in several scientific areas: data p
The optimization process ended when the objective function satisfied the stopping criteria or reached the maximum number of iterations. The global best values determined the optimal values when the framework was terminated. Figure 1. Overview of the framework linking the FD-BEM and the optimization ...
In practice, infinity is not reached due to stopping criteria for convergence of the iterative method used for obtaining the ME‑PDF. Figure 2. Field of the non-Gaussian MI I n g , 4 along 6 bivariate cross-sections of the set of allowed moments. Two varying moments are featured in ...