Alternatively a Bayesian Model Merging principle may be adopted such that product of model prior and likelihood measure associated with the model is maximized.
Influence maximization is the task of finding a set of seed nodes in a social network such that the influence spread of these seed nodes based on certain influence diffusion model is maximized.
The idea of HMMI for audio-to-visual conversion is to estimate the visual features based on the trained AV-HMM, in such a way that the probability that the whole audio-visual observation has been generated by the model is maximized, that is Õ v = arg max { O v P ( O a, O v | λ av ) }, (2).
When the "truly" homogeneous subsets have been identified, the iteration will stop as the predictive ability of the OPLS-DA model is maximized.
However, by no means does this approach guarantee that the optimal number of branch partitions are used and that the corresponding increase in model fit over an independent evolutionary model is maximized.
In addition, in[10], the one step ahead expected information from the target kinematic model was maximized using the appropriate waveform selection.
The likelihood for each model was maximized by modifying the parameter values and a likelihood ratio test performed to determine whether model no. 1 or no. 2 best described the data.
While it is essential to be able to effectively transfer information to the community at large it is imperative that the educational quality of the product that a training program produces (lay health advisor, witness role model) be maximized through well integrated multifaceted approaches.
In contrast the difference in individual DT models is maximized in DF such that a best ensemble is usually realized by combining only a few DT models (i.e., four or five).
Specifically, CONGA identifies a set of orthologous genes to delete such that the flux difference in a reaction of interest (e.g., growth rate) between the two models is maximized.
