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Gu et al. [17] use a weighted nuclear norm minimization algorithm for denoising.
In this paper, we propose the reweighted l 1 minimization algorithm for image deblurring.
Xie et al. [37] use a weighted Schatten p-norm minimization algorithm for denoising.
In this paper, a new reweighted l 1 minimization algorithm for image deblurring is proposed.
In this article, we propose a weighted ℓ2,1 minimization algorithm for jointly-sparse signal recovery problem.
The proposed cost model is applied within a cost minimization algorithm for making service placement decisions in clouds.
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Neural minimization algorithms for solving the finite difference equations are presented.
This paper demonstrates both theoretically, through theorem proofs, and experimentally, that existing minimization algorithms for ESOP (Exclusive or Sum Of Products) expressions can be successfully used for minimizing ESCT (Exclusive or Sum of Complex Terms) expressions as well.
This paper introduces an approximate geometric gradient descent procedure over these varieties, which is powered by minimization algorithms for the frame operator distance and recent characterizations of these varietiesʼ tangent spaces.
Our algorithms extend the free energy minimization algorithm of Zuker & Stiegler for secondary structure prediction, and the sub-optimal folding algorithm by Wuchty et al. Implementations of our algorithms are freely available in the package MultiRNAFold (http://www.rnasoft.ca/download.html).html
The ABNR minimization algorithm was used for energy minimizations.
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