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This solves the optimization problem of worst-case performance by maximizing the approximate negentropy subject to the SOCP constraint.
This algorithm is based on the assumption of the independence and non-Gaussianity of the sources before maximizing the approximate negentropies of those ones [30, 33].
ICA is a higher-order, statistical signal processing technique for BSS and features extraction by maximizing the approximate negentropy of input signals, which is significantly less sensitive to the colored noise model than the SOS-based EVD [24].
The proposed differential detection maximizing the approximate negentropy that is subject to worst-case performance is still reasonably applied to the largely norm-bounded mismatch Δe and can be described in the following form: maximize w E G w H y ˜ 2, subject to min Δ e ≤ δ w H c ^ 1 ≥ 1. (18).
In the second step updates of the variance parameters are obtained by maximizing the approximate restricted log-likelihood.
The Lagrange multiplier functions obey the final condition λ(T) = 0. Estimation of the parameters A and b can be done directly by maximizing the approximate marginal likelihood Eq[ logp y|r,Ω)].
Similar(53)
Finally, we find a joint structure that maximizes the approximate estimator (4).
To maximize the approximate population likelihood in Eq. (10), we have to solve a nested optimization problem.
IPknot predicts a pseudoknotted secondary structure that maximizes the approximate expected gain function (3), which represents the expectation of the (weighted) number of true predictions of base pairs under a given probability distribution.
For the problem of maximizing the service level, we approximate the objective with the largest inscribing sphere and provide a linear program formulation.
Because we are interested in maximizing the accuracy on a naive test set, we approximate this set by performing internal cross-validation for each method.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com