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- W2000748685 abstract "This paper brings together and discusses theory and applications of methods, identified and labelled as row-action methods, for linear feasibility problems (find $x in {bf R}^n $, such that $Ax leqq b$), linearly constrained optimization problems (minimize $f(x)$, subject to $Ax leqq b$) and some interval convex programming problems (minimize $f(x)$, subject to $c leqq Ax leqq b$). The main feature of row-action methods is that they are iterative procedures which, without making any changes to the original matrix A, use the rows of A, one row at a time. Such methods are important and have demonstrated effectiveness for problems with large or huge matrices which do not enjoy any detectable or usable structural pattern, apart from a high degree of sparaseness. Fields of application where row-action methods are used in various ways include image reconstruction from projection, operations research and game theory, learning theory, pattern recognition and transportation theory. A row-action method for the nonlinear convex feasibility problem is also presented." @default.
- W2000748685 created "2016-06-24" @default.
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- W2000748685 date "1981-10-01" @default.
- W2000748685 modified "2023-10-14" @default.
- W2000748685 title "Row-Action Methods for Huge and Sparse Systems and Their Applications" @default.
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- W2000748685 doi "https://doi.org/10.1137/1023097" @default.
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