Sentence examples for using expectation from inspiring English sources
"For millennia, medicine was basically placebo – by using expectation, magicians used the will to heal," he says.
For this purpose, we present a maximum likelihood based approach to integrate the multi-rate output data in the model building task, using Expectation Maximization algorithm.
Two different set of features which are complement to each, other, Mel Frequency Cepstral Coefficient (MFCC) and Inverted Mel Frequency Cepstral Coefficient (MFCC) features are obtained for each speaker and are trained using Expectation Maximization algorithm.
However, the algorithms of mixture model using expectation maximization (EM) technique are still too slow to deal with real million-node networks, since they compute hidden variables on the entire network in each iteration.
In this adaptation, the parameters of a universal background model (UBM), which are estimated from all video clips using expectation maximization (EM) algorithm, are utilized as the prior distribution for Gaussian means.
They proposed Generative Model of Labels, Abilities, and Difficulties (GLAD) which estimates these parameters using Expectation Maximization (EM) probabilistic models and evaluate tasks output in a way that experts' outputs count more.
It operates in an iterative mode using expectation-maximization (EM) algorithm.
The number of patterns which represents the model complexity are determined by Bayesian Information Criteria (BIC), while other parameters of GMM are estimated by using Expectation-Maximization algorithm under the Maximum Likelihood criteria, based on the monitored cable tension force.
Maximum likelihood semiblind joint channel estimation and equalization for doubly selective channels and single-carrier systems is proposed using expectation-maximization (EM) algorithm in the paper by G. Kutz and D. Raphaeli.
The interest of this paper is to improve the performance of single neural network (SNN) by dividing the fault pattern space into a few smaller sub-spaces using Expectation-Maximization (EM) clustering technique and triggering the right local classifier by designing a supervisor agent.
The method proposed in this paper dynamically allocates relevance to inputs by using expectations of their future values.
