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In Figure 6 the selected parameter values S N pr for the primal and S N du for the dual problems, respectively, are shown; in each case Ξ train is a uniform random sample of size n train = 1, 000.
Here Ξ train is a uniform random sample of size n train = 1, 000 and the RB tolerance is ϵ tol ∗ = 10 − 2. Figure 6 'Couette-Graetz' conduction-convection problem: selected parameter values S N pr for the primal (left) and S N du for the dual (right) in the parameter space.
Here Ξ train is a uniform random sample of size n train = 1, 000 and the RB tolerance is ε tol ∗ = 10 − 2. In Figures 12 and 13 some representative solutions for selected values of parameters are reported, for both t = Δ t and t = T.
We start with a uniform random sample containing n observations drawn from.
SWIFT then selects a small, uniform, random sample of the total dataset, and identifies initial clusters by the Expectation-Maximization (EM) algorithm for Gaussian mixture modeling (GMM).
We used the software SeqGrapheR (Novãk et al. 2010) to analyze the TE content of the D. simulans genome directly from a uniform random sample of 900 k reads obtained from the 2012 genome project (SRA SRX159034) (Hu et al. 2013).
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We can use uniform random sampling, which selects elements with equal probability from P ́ T ( v ).
Uniform random sampling of the steady-state flux space allows for the unbiased appraisal of its contents.
After delivery, microscopical fields on formalin-fixed, trichrome-stained histological sections of each placenta were obtained by multistage systematic uniform random sampling.
In Algorithm 2, it first computes | P ́ T ( v ) | (step 1) and then estimates σ T (v) by uniform random sampling.
The number of observations of the final clusters is equalized by applying a uniform random sampling on the data points, so that the training is balanced.
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