Sentence examples for iteration based on the from inspiring English sources
In this paper, we present a modified implicit method, which adjusts the parameter automatically per iteration, based on the message from former iterates.
In co-training [which belongs to a larger class of semi-supervised learning methods (Chapelle et al., 2006)], two models are iteratively improved by continuously increasing the training (labeled) set at each iteration based on the agreement of the models on the unlabeled examples.
It updates the weights in every iteration based on the error calculated for that iteration.
The idea is to vary the step-size at each iteration based on the error performance.
The parameter λ(i is the damping factor, obtained at every iteration based on the trust region approach [20, 30].
At each iteration, based on the sensitivity analysis all the free nodes are moved along certain directions to reduce the compliance.
Thus, an MNB turbo-decoder equipped with a mechanism to stop the iterations based on the minAPP criterion (easily implementable in practice) performs on average 1.5 more iterations than the one based on the genie criterion (not applicable in practice).
In Section 4, we prove results for the iterations based on the exact data and, in Section 5, the error analysis for the noisy data case is proved.
The Lanzcos method of minimized iterations, based on the integral equation of beam vibrations, is used to obtain intermediate modes with the distributions along the beam of its mass and rigidity as data.
In both cases, we show that pure fixed-point iterations based on the parallel execution of the solvers do not lead to good results, but the combination of parallel solver execution and so-called quasi-Newton methods yields very efficient and robust methods.
To further handle sample impoverishment problem suffered by conventional PF, Zhang et al. [9] propose a swarm intelligence-based PF tracking algorithm, where particles are firstly propagated through the state transition model, and then corporately evolved according to particle swarm optimization (PSO) iterations based on the cognitive and social aspects of particle populations.
