Please use this identifier to cite or link to this item: https://doi.org/10.15480/882.4875
Publisher DOI: 10.1007/978-3-031-21534-6_6
Title: Recent advances in practical data reduction
Language: English
Authors: Abu-Khzam, Faisal N. 
Lamm, Sebastian 
Mnich, Matthias  
Noe, Alexander 
Schulz, Christian 
Strash, Darren 
Issue Date: 18-Jan-2023
Publisher: Springer Nature Switzerland
Source: Algorithms for Big Data (2023)
Abstract (english): 
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.
URI: http://hdl.handle.net/11420/14591
DOI: 10.15480/882.4875
Institute: Algorithmen und Komplexität E-11 
Document Type: Chapter (Book)
Project: Kernelisierung für große Datenmengen 
Funded by: Deutsche Forschungsgemeinschaft (DFG) 
Peer Reviewed: Yes
License: CC BY 4.0 (Attribution) CC BY 4.0 (Attribution)
Part of Series: Lecture notes in computer science 
Volume number: 13201
Is Part of: 978-3-031-21534-6
Is new version of: 10.15480/882.4144
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