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Titlebook: Algorithm Theory -- SWAT 2012; 13th Scandinavian Sy Fedor V. Fomin,Petteri Kaski Conference proceedings 2012 Springer-Verlag Berlin Heidelb

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https://doi.org/10.1007/978-3-658-36256-0. contains at least one end-point of each edge and such that . induces a connected subgraph. For this problem we present a deterministic algorithm running in .(2.poly(.)) time and polynomial space, improving over the previous-best .(2.4882.poly(.)) time deterministic algorithm and .(2.poly(.)) time
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https://doi.org/10.1007/978-3-658-36256-0ph and the subgraph induced on the other is an independent set. We study the problem of deleting the minimum number of vertices or edges from a given input graph so that the resulting graph is split.We initiate a systematic study and give efficient fixed-parameter algorithms and polynomial sized ker
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,Die militärischen Mittel der Politik,ces (except perhaps their end-vertices). The . problem is to test whether a graph . with . pairs of specified vertices (..,..) contains . mutually induced paths .. such that .. connects .. and .. for . = 1,…,.. This problem is known to be NP-complete already for . = 2. We prove that it can be solved
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Technikberatung in der Demokratiemoving distance of the sensors is minimized. Previously, it was an open question whether this problem on sensors with arbitrary sensing ranges is solvable in polynomial time. We settle this open question positively by giving an .(..log.loglog.) time algorithm. Further, if all sensors have the same-s
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https://doi.org/10.1007/978-3-663-09582-8ference at ., denoted .(.), is the number of antennas that cover ., and the interference of a communication graph . = (.,.) is .(.) =  max {.(.) : . ∈ .}. In this paper we address the question in its title. That is, we study several variants of the following problem: What is the minimum interference
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