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Article . 2023 . Peer-reviewed
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Journal of Computer and System Sciences
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https://dx.doi.org/10.48550/ar...
Article . 2023
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Dynamic programming on bipartite tree decompositions

Authors: Lars Jaffke; Laure Morelle; Ignasi Sau; Dimitrios M. Thilikos;

Dynamic programming on bipartite tree decompositions

Abstract

We revisit a graph width parameter that we dub bipartite treewidth (btw). Bipartite treewidth can be seen as a common generalization of treewidth and the odd cycle transversal number, and is closely related to odd-minors. Intuitively, a bipartite tree decomposition is a tree decomposition whose bags induce almost bipartite graphs and whose adhesions contain at most one "bipartite" vertex, while the width of such decomposition measures the number of "non-bipartite" vertices in a bag. We provide para-NP-completeness results and develop dynamic programming techniques to solve problems on graphs of small btw. In particular, we show that $K_t$-Subgraph-Cover, Weighted Independent Set, Odd Cycle Transversal, and Maximum Weighted Cut are $FPT$ parameterized by btw. We also provide the following dichotomy when $H$ is a 2-connected graph: if $H$ is bipartite, then $H$-Subgraph/Induced-Subgraph/Odd-Minor/Scattered-Packing is para-NP-complete parameterized by btw while, if $H$ is non-bipartite, then the problem is solvable in XP-time.

Presented in IPEC 2023

Countries
Germany, Norway
Keywords

dynamic programming, FOS: Computer and information sciences, F.2.2; G.2.2, bipartite graphs, Data Structures and Algorithms, tree decomposition, 05C85, 68R10, 05C75, 05C83, 05C75, 05C69, maximum cut, vertex cover, 004, odd cycle transversal, independent set, packing, Data Structures and Algorithms (cs.DS), odd-minors

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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