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We minimize a deterministic regularized function in a Multilayer Perceptron (MLP) with no training and follow a back-propagation algorithm with the L1 and L2 norm-based regularizers.
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It is a stochastic process in nature, but its optimal control is based on the solution to a related deterministic optimal tracking problem to minimize a quadratic cost objective restricted by linear dynamics.
Unlike the stability optimization methods for deterministic problems, which minimize the spectral abscissa, our approach shows better robust properties based on a more realistic model, where the uncertainty is taken into account by minimizing an objective function, consisting of the mean of the spectral abscissa with a variance penalty.
Each sample can only be in a deterministic cluster to minimize the sum of squares within a group, i.e., each sample x p can only be allocated to a cluster ( {S}_i^{(t)} ).
Then, a deterministic algorithm for minimizing the expected error of a feedforward network of random weights is presented.
We then consider a deterministic scheme for minimizing the out of focus light in the reconstructed image by including information from the first or zero order passband depending on which has the largest axial OTF support at each frequency (Max kz-SIM).
The starting point is constituted by a deterministic model able to minimize long-term total costs of the system, accounting also for design parameters affecting expected lives of relevant components.
The model and discretization are applied to both the deterministic and the stochastic continuous restricted location problem, where the latter is converted into a deterministic equivalent problem by minimizing the expected value of the objective function weighted by the probabilities of scenarios.
This paper proposes two optimization algorithms for the RS-γ charts, i.e. by minimizing (i) the average run length (ARL) for a deterministic shift size and (ii) the expected ARL over a process shift domain.
In this work, we have defined a deterministic quasi-potential that is minimized along a temporal trajectory followed by a gene network, and used it to quantitatively derive the corresponding epigenetic landscape.
In fact, AECL had proposed such a deterministic detector layout optimization (DLO) technique to minimize the number of ROP detectors in 1998.
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CEO of Professional Science Editing for Scientists @ prosciediting.com