Sentence examples for a generalized expectation from inspiring English sources

An ML approach has been presented for estimating the average RCS, and a numerical solution to the approach has been proposed based on a generalized expectation maximization algorithm.

In this paper, a maximum-likelihood (ML) approach is presented for estimating the average RCS, and a numerical solution to the approach is proposed based on a generalized expectation maximization (GEM) algorithm.

cnvHap updates the positions of these cluster positions within a generalized expectation maximization framework and then reports the per-sample copy number genotypes (Fig. 3).

As well it may create a generalized expectation that HIV-positive people will always disclose, and therefore condom use is unnecessary because non-disclosure comes to signify HIV-negative status.

The network layout algorithm used is a Generalized Expectation-Maximization (GEM) algorithm described by Arne et al. [ 36].

As previously described, the parameters of the HMM are estimated using a generalized expectation-maximization algorithm and the most likely CNV segmentation for the trained model is obtained by the Viterbi algorithm.

A Gibbs sampler is used to perform Markov chain Monte Carlo estimation (MCMC) and a generalized expectation-maximization algorithm as a faster alternative for maximum a posteriori point estimation.

Expectation theory defines trust as "a generalized expectancy held by an individual that the word, promise, oral or written statement of another individual or group can be relied upon" (Rotter 1980).

In this work, we consider a threshold approach of binary, ordinal, and censored Gaussian observations for Bayesian multilocus association models and Bayesian genomic best linear unbiased prediction and present a high-speed generalized expectation maximization algorithm for parameter estimation under these models.

For most of us who have been sepsis investigators for a long time, the generalized expectation is that the earlier we intervene the better the chances that one can interrupt the sepsis cascade, and so on.

We develop an efficient learning algorithm, based on generalized expectation maximization (EM), to optimize a bound on the likelihood termed free energy (Neal and Hinton, 1998).