Meanwhile, this work also investigated the application of regularization techniques, the selection of optimal regularization parameter, and the use of a local search technique for binary problems.
From these results it can be observed that increase of the number of hidden layers and neurons, combined with application of regularization, has a substantial effect on the performance of DNN.
In this paper we show that theoretical results from the field of compressed sensing (CS) supply a rigorous quantitative framework for the application of regularization methods to GWAS.
Furthermore, application of dropout regularization on the performance, configurations C G, was also found to affect the performance, when comparing to non-regularized networks.
The application of the regularization to an existing subgrid scale model is shown to remove high wavenumber errors while maintaining agreement with Direct Numerical Simulations (DNS) of forced and decaying isotropic turbulence.
In this work, we focus on the application of L1 regularization to a class of inverse problems; relaxation-relaxation, T1 T2, and diffusion-relaxation, D T2, correlation experiments in NMR, which have found widespread applications in a number of areas including probing surface interactions in catalysis and characterizing fluid composition and pore structures in rocks.
Many examples can be found in the literature for the application of the regularization, such as determining the slip distribution of fault systems (Aktuğ et al., 2010), ionospheric tomography (Howe et al., 1998), and tropo-spheric tomography (Flores et al., 2000).
However, when comparing the quality of solutions derived from zero- and first-order regularization, we conclude the application of first-order regularization produces better results, and the accuracy of the corresponding model reaches 1.6 cm.
Application of the proposed regularization strategies to more complex optimization problems of physical and engineering relevance is also discussed.
Third, the EnKF offers several interesting opportunities to apply SP techniques, e.g., via the application of bootstrap or regularization methods in the EnKF gain computation.
The second step is an innovative application of nonsmooth mixed regularization, and it accurately resolves the scatterer size as well as intensities.
