A. J. Kearsley. Matrix-free algorithm for the large-scale constrained trust-region subproblem. Optimization Methods and Software, 21(2):233-245, April 2006.M. Rojas, S.A. Santos and D.C. Sorensen. A matrix-free algorithm for the large-scale trust-region subproblem. Technical Report TR99...
Our second contribution is a matrix-free algorithm to find a minimizer of the regularized reaper which is also suited for high-dimensional data. The algorithm couples a primal-dual minimization approach with a thick-restarted Lanczos process. This appears to be the first efficient convex variational...
A matrix-free line-search algorithm for nonconvex optimizationnonlinear programmingnonconvex large-scale problemstrust-region methodsconjugate gradient methodHessian-free methodsmachine learning90C0690C3090C2665K05In this paper, we have developed a new algorithm for solving nonconvex large-scale problems....
In this paper, a new kind of inverse-of-matrix-free Kalman filtering algorithm is proposed, which has both high numerical. . . 本文提出了一种无矩阵求逆的最优卡尔曼滤波计算方法,该算法数值稳定性强,且计算量也比较小。 epub.cnki.net 2. A New Kind of Inverse-of-matrix-free Kalman Filtering...
Indexing Vectors Let’s start with the simple case of a vector and subscripts. v = [16 5 9 4 2 11 7 14]; The subscript can be a single value: v(3)% Extract the third elementans = 9 Or a subscript can itself be another vector. ...
Change the options of the algorithm using optimoptions('fminunc'). If you don’t specify the options, then LinearMixedModel uses the default options of optimoptions('fminunc') with 'Algorithm' set to 'quasi-newton'. Example: 'Optimizer','fminunc' OptimizerOptions— Options for optimization ...
“Matrix Solver Step by Step” Linear Algebra learning tool and a Matrix Calculator: * Performs most commonly used matrix calculations and decompositions (see list below). * Demonstrates and explains algorithm steps for almost all the functions. ...
Analysis of LC-MS proteomic data was performed in Proteome Discoverer 2.5 (Thermo Scientific) utilizing the Sequest HT search algorithm with the mouse proteome (UniProt UP000000589; 55,485 proteins covering 21,989 genes with a BUSCO assessment of 99.8% genetic coverage). Search parameters were as...
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This section describes a typical process for writing an efficient sparse matrix program using the tools provided by this invention. The program is one to compute the LU factorization, with partial pivoting, of a sparse matrix. The algorithm used is a "left-looking" column-oriented algorithm; see...