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nhigham.com | ||
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www.sirver.net
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www.jeremykun.com
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| | | | | The singular value decomposition (SVD) of a matrix is a fundamental tool in computer science, data analysis, and statistics. It's used for all kinds of applications from regression to prediction, to finding approximate solutions to optimization problems. In this series of two posts we'll motivate, define, compute, and use the singular value decomposition to analyze some data. (Jump to the second post) I want to spend the first post entirely on motivation and background. | |
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nla-group.org
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| | | | | by Sven Hammarling and Nick Higham It is often thought that Jim Wilkinson developed backward error analysis because of his early involvement in solving systems of linear equations. In his 1970 Turing lecture [5] he described an experience, during world war II at the Armament Research Department, of solving a system of twelve linear equations | |
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theweek.com
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| | | Anh Duong is an unlikely weapons genius, says Laura Blumenfeld in The Washington Post. A suburban mother of four, she doesn't let her kids read Harry Potter books because they're too violent. "We don't want our kids to think violence is the answer,'' she | ||
