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To maximize the approximate population likelihood in Eq. (10), we have to solve a nested optimization problem.
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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.
Finally, we find a joint structure that maximizes the approximate estimator (4).
However, estimation of the hierarchical prior parameters by maximizing the approximate marginal likelihood also makes the model susceptible to overfitting by encouraging a small set of samples to be randomly, and often confidently, assigned to unnecessary components of the model.
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)].
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.
We should notice that maximizing the approximate estimator (4) is equivalent to maximizing the sum of: (i) the sum of the base-pairing probabilities p(a ) ij larger than θ s = 1/(γ s +1); (ii) the sum of the base-pairing probabilities p(b ) ij larger than θ s ; and (iii) the sum of the hybridization probabilities q ij larger than θ h = 1/(γ h +1).
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