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The use of a regularized friction law allows obtaining good convergence of such models.
The use of a regularized contact model in the underlying state problem makes it possible to use efficient smooth optimization algorithms for the systematic synthesis of CCMs.
We present a least-squares formulation with improved velocity pressure coupling, based on the use of a regularized divergence-free constraint.
In all other instances, the use of a regularized estimator is absolutely vital (e.g., the Stein-type shrinkage estimator of [ 20]) in order to improve efficiency and to guarantee positive definiteness.
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Earlier work on the topic makes use of a lasso-like regularized regression framework.
These regulators and their corresponding posterior probabilities of activity are used in a regularized regression framework to predict response.
We introduce a new version of the MRMR criterion using a regularized redundancy measure of Section 3.1 and a robust relevance measure of Section 3.2.
Another multi-task learning method making use of regularized regression is the trace norm regularized method proposed by Chen et al. [43].
The results of this study show that use of the regularized constitutive models significantly improved the accuracy of response predictions.
We made use of the regularized regression based multi-task learning approaches using five personality traits and four leadership traits from the ELEA dataset and five personality traits from the VLOG dataset as tasks.
Quine and Choi [15] made use of zeta regularized products to compute det ′ Δ n and the determinant of the conformal Laplacian, det ( Δ S n + n ( n − 2 ) / 4 ).
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