Sentence examples for develop a regularization from inspiring English sources
We develop a regularization smoothing predictor-corrector method for solving the problem by modifying and extending the method in [13].
In this paper we develop a regularization technique for CHS to any arbitrary order and use its first-order regularization to show that in the case of the 2D unit disk, although CHS misrepresents the boundary layer behaviour, it does give the correct boundary condition for the interior macroscopic (Laplace) equation.
This important property can be exploited to develop a new regularization scheme.
In this study, we develop a new model regularization method by introducing an edge-preserving smoothing operator to detect the model edges in traveltime tomography.
Considering the sparsity of force in the time domain or in other basis space, we develop a general sparse regularization method based on minimizing l1-norm of the coefficient vector of basis functions.
We therefore developed a novel regularization scheme for the inversion problem that uses discontinuity, sparsity, and smoothness constraints.
The algorithm for change detection of piecewise-constant AR models developed in this article belongs to the first class of methods, and its first novelty consists in developing a new regularization function which encourages piecewise-constant TV-AR coefficients while being convex and continuous; hence, it can afford efficient convex optimization solvers.
Using a simplified physical model that ignores 3D effects of the complete structure, we develop a novel inter-slice regularization strategy to obtain global regularity.
Here we develop a method incorporating the principle of regularization for identification of an optimal pathway in gene regulatory networks starting from a given gene to a target gene.
Given this setup, we develop a framework for low-rank matrix estimation that allows us to transform noise models into regularization schemes via a simple parametric bootstrap.
We develop a new proof technique showing that early stopping the algorithm instead may also yield an optimal estimator without explicit regularization.
