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Algorithm Selection on a Meta Level
[article]
2021
arXiv
pre-print
The problem of selecting an algorithm that appears most suitable for a specific instance of an algorithmic problem class, such as the Boolean satisfiability problem, is called instance-specific algorithm selection. Over the past decade, the problem has received considerable attention, resulting in a number of different methods for algorithm selection. Although most of these methods are based on machine learning, surprisingly little work has been done on meta learning, that is, on taking
arXiv:2107.09414v1
fatcat:4dygwremnndlxjot6l5re7s7ba