Beyond the Worst-Case Analysis of Algorithms (Introduction)
July 26, 2020 Β· Declared Dead Β· π arXiv.org
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Authors
Tim Roughgarden
arXiv ID
2007.13241
Category
cs.DS: Data Structures & Algorithms
Cross-listed
stat.ML
Citations
4
Venue
arXiv.org
Last Checked
4 months ago
Abstract
One of the primary goals of the mathematical analysis of algorithms is to provide guidance about which algorithm is the "best" for solving a given computational problem. Worst-case analysis summarizes the performance profile of an algorithm by its worst performance on any input of a given size, implicitly advocating for the algorithm with the best-possible worst-case performance. Strong worst-case guarantees are the holy grail of algorithm design, providing an application-agnostic certification of an algorithm's robustly good performance. However, for many fundamental problems and performance measures, such guarantees are impossible and a more nuanced analysis approach is called for. This chapter surveys several alternatives to worst-case analysis that are discussed in detail later in the book.
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