Fedor V Fomin, Daniel Lokshtanov, Saket Saurabh, Meirav Zehavi

Kernelization

Theory of Parameterized Preprocessing

• Gebundenes Buch

Produktbeschreibung

A complete introduction to recent advances in preprocessing analysis, or kernelization, with extensive examples using a single data set.

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Produktdetails

• Verlag: Cambridge University Press
• Seitenzahl: 528
• Erscheinungstermin: 28. Februar 2019
• Englisch
• Abmessung: 233mm x 161mm x 32mm
• Gewicht: 869g
• ISBN-13: 9781107057760
• ISBN-10: 1107057760
• Artikelnr.: 53170551

Autorenporträt

Fedor V. Fomin is Professor of Computer Science at the Universitetet i Bergen, Norway. He is known for his work in algorithms and graph theory. He has co-authored two books, Exact Exponential Algorithms (2010) and Parameterized Algorithms (2015), and received the EATCS Nerode prizes in 2015 and 2017 for his work on bidimensionality and Measure and Conquer.

Inhaltsangabe

1. What is a kernel?
Part I. Upper Bounds: 2. Warm up
3. Inductive priorities
4. Crown decomposition
5. Expansion lemma
6. Linear programming
7. Hypertrees
8. Sunflower lemma
9. Modules
10. Matroids
11. Representative families
12. Greedy packing
13. Euler's formula
Part II. Meta Theorems: 14. Introduction to treewidth
15. Bidimensionality and protrusions
16. Surgery on graphs
Part III. Lower Bounds: 17. Framework
18. Instance selectors
19. Polynomial parameter transformation
20. Polynomial lower bounds
21. Extending distillation
Part IV. Beyond Kernelization: 22. Turing kernelization
23. Lossy kernelization.