Results 11 to 20 of about 82,972,811 (208)
Alternative methods for representing the inverse of linear programming basis matrices [PDF]
, 1988 Methods for representing the inverse of Linear Programming (LP) basis matrices are closely related to techniques for solving a system of sparse unsymmetric linear equations by direct methods.
Mitra, G, Tamiz, M
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Solving large scale linear programming [PDF]
, 1993 The interior point method (IPM) is now well established as a competitive technique for solving very large scale linear programming problems. The leading variant of the interior point method is the primal dual - predictor corrector algorithm due to ...
Levkovitz, R, Mitra, G, Hafsteinsson, H
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Solving large scale linear programming problems [PDF]
, 1993 The interior point method (IPM) is now well established as a computationaly com-petitive scheme for solving very large scale linear programming problems. The leading variant of the IPM is the primal dual predictor corrector algorithm due to Mehrotra. The
Levkovitz, R
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Large-Scale Visualization of Sparse Matrices [PDF]
, 2014 An efficient algorithm for parallel acquisition of visualization data for large sparse matrices is presented and evaluated both analytically and empirically.
Tvrdik, P. +3 more
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Sparse Diagonal Matrix Adaptive SpMV Optimization Method for GPU [PDF]
Jisuanji gongchengSparse Matrix-Vector multiplication (SpMV) is the computational core and bottleneck of sparse linear systems, and its computational efficiency affects the overall performance of iterative solvers.
WANG Yuhua, HE Junfei, ZHANG Yuqi, LAN Haiyan, CAO Linlin
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Adapting the interior point method for the solution of LPs on serial, coarse grain parallel and massively parallel computers [PDF]
, 1990 In this paper we describe a unified scheme for implementing an interior point algorithm (IPM) over a range of computer architectures. In the inner iteration of the IPM a search direction is computed using Newton's method.
Levkovitz, R +7 more
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IEEE Access, 2023 Diversity measures exploited by blind source separation (BSS) methods are usually based on either statistical attributes/geometrical structures or sparse/overcomplete (underdetermined) representations of the signals.
Muhammad Usman Khalid +2 more
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Equivalence of replica and cavity methods for computing spectra of sparse random matrices [PDF]
Physical Review E, 2011 We show by direct calculation that the replica and cavity methods are exactly equivalent for the spectrum of Erdos-Renyi random graph. We introduce a variational formulation based on the cavity method and use it to find approximate solutions for the density of eigenvalues. We also use this variational method for calculating spectra of sparse covariance
openaire +3 more sources
Embedded Zassenhaus Expansion to Splitting Schemes: Theory and Multiphysics Applications
International Journal of Differential Equations, 2013 We present some operator splitting methods improved by the use of the Zassenhaus product and designed for applications to multiphysics problems. We treat iterative splitting methods that can be improved by means of the Zassenhaus product formula, which ...
Jürgen Geiser
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A new generalized shift-splitting method for nonsymmetric saddle point problems
Advances in Mechanical Engineering, 2022 Recently, Huang and Huang [ Journal of Computational and Applied Mathematics , 328 (2018) 381–399] proposed a modified generalized shift-splitting preconditioned (denoted by MGSSP) method for solving large sparse saddle point problems, and gave the ...
Tao Wei, Li-Tao Zhang
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