Recent advances in practical data reduction

First published in
Lecture notes in computer science 
Number in series
13201 LNCS
Start Page
97
End Page
133
Citation
Algorithms for Big Data (2023)
Publisher DOI
10.1007/978-3-031-21534-6_6
Scopus ID
2-s2.0-85147433581
Publisher
Springer Nature Switzerland
Peer Reviewed
true
Is Part Of
isbn:978-3-031-21534-6
Is New Version of
10.15480/882.4144
Over the last two decades, significant advances have been made in the design and analysis of fixed-parameter algorithms for a wide variety of graph-theoretic problems. This has resulted in an algorithmic toolbox that is by now well-established. However, these theoretical algorithmic ideas have received very little attention from the practical perspective. We survey recent trends in data reduction engineering results for selected problems. Moreover, we describe concrete techniques that may be useful for future implementations in the area and give open problems and research questions.
DDC Class
004: Informatik
510: Mathematik