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• W1009047 abstract "There are many applications and problems in science and engineering that require large-scale numerical simulations and computations. The issue of choosing an appropriate method to solve these problems is very common, however it is not a trivial one, principally because this decision is most of the times too hard for humans to make, or certain degree of expertise and knowledge in the particular discipline, or in mathematics, are required. Thus, the development of a methodology that can facilitate or automate this process and helps to understand the problem, would be of great interest and help. The proposal is to utilize various statistically based machine-learning and data mining techniques to analyze and automate the process of choosing an appropriate numerical algorithm for solving a specific set of problems (sparse linear systems) based on their individual properties." @default.
• W1009047 created "2016-06-24" @default.
• W1009047 creator A5035666796 @default.
• W1009047 date "2007-01-01" @default.
• W1009047 modified "2023-09-25" @default.
• W1009047 title "Statistical and Machine Learning Techniques Applied to Algorithm Selection for Solving Sparse Linear Systems" @default.
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