Open AccessBook
Parameterized complexity theory
Jörg Flum,Martin Grohe +1 more
TLDR
Fixed-Parameter Tractability.Abstract:
Fixed-Parameter Tractability.- Reductions and Parameterized Intractability.- The Class W[P].- Logic and Complexity.- Two Fundamental Hierarchies.- The First Level of the Hierarchies.- The W-Hierarchy.- The A- Hierarchy.- Kernelization and Linear Programming Techniques.- The Automata-Theoretic Approach.- Tree Width.- Planarity and Bounded Local Tree Width.- Homomorphisms and Embeddings.- Parameterized Counting Problems.- Bounded Fixed-Parameter Tractability.- Subexponential Fixed-Parameter Tractability.- Appendix, Background from Complexity Theory.- References.- Notation.- Index.read more
Citations
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Book ChapterDOI
Approximation algorithms for intersection graphs
TL;DR: Three complexity parameters that in some sense measure how chordal-like a graph is are studied to construct simple polynomial-time approximation algorithms with constant approximation ratio for many NP-hard problems, when restricted to graphs for which at least one of the three complexity parameters is bounded by a constant.
Book ChapterDOI
Genomic Scaffold Filling: A Progress Report
TL;DR: The genomic scaffold filling problem has attracted a lot of attention since 2010 and is NP-complete and APX-hard, and admits a 1.2-approximation approach.
Book ChapterDOI
A parameterized complexity tutorial
TL;DR: The article was prepared for the LATA 2012 conference where I will be presenting two one and half hour lectures for a short tutorial on parameterized complexity.
Journal ArticleDOI
A single-exponential FPT algorithm for the K 4 -minor cover problem
TL;DR: An efficient FPT algorithm for the K 4 -minor cover problem is provided that combines iterative compression with protrusion reduction and branching and extends previous algorithms for Vertex Cover and Feedback Vertex Set.
Proceedings ArticleDOI
Pareto Optimal Allocation under Uncertain Preferences
TL;DR: In this paper, the authors consider the problem of assigning an assignment with the highest probability of being Pareto optimal under two uncertainty models: (1) the lottery model in which each agent has an independent probability distribution over linear orders and (2) the joint probability model that involves a joint probability distributions over preference profiles.