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Titlebook: Algorithms and Computation; 17th International S Tetsuo Asano Conference proceedings 2006 Springer-Verlag Berlin Heidelberg 2006 AAC.Schedu

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发表于 2025-3-21 16:45:45 | 显示全部楼层 |阅读模式
期刊全称Algorithms and Computation
期刊简称17th International S
影响因子2023Tetsuo Asano
视频video
学科分类Lecture Notes in Computer Science
图书封面Titlebook: Algorithms and Computation; 17th International S Tetsuo Asano Conference proceedings 2006 Springer-Verlag Berlin Heidelberg 2006 AAC.Schedu
Pindex Conference proceedings 2006
The information of publication is updating

书目名称Algorithms and Computation影响因子(影响力)




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书目名称Algorithms and Computation网络公开度




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书目名称Algorithms and Computation被引频次




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发表于 2025-3-21 20:22:21 | 显示全部楼层
https://doi.org/10.1007/978-3-642-74101-2lems: . and some variations, counting the number of maximum weighted independent sets. We also briefly discuss how similar techniques can be used to design parameterized algorithms. As an example, we give fastest known algorithm solving .-. problem.
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Johannes Willms,Johann Weichbrodtdegree of any vertex or the number of edges in either the input graph or its complement. We further provide multiple types of recursive, deterministic algorithms for trees and forests, and provide an improvement for forests that makes use of randomization.
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https://doi.org/10.1007/978-3-642-84612-0ting targets. This is a significant improvement on . ≤.(. + 2) given by Fomin et.al. [2004] on graphs with small .-octopus... Dominating target, .-octopus, Dominating set, Dominating-pair graph, Steiner tree.
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Die Dynamik der ProduktionsfunktionOn a line metric with . uniformly spaced points, our algorithm yields the first . and runs in quasi-polynomial time .(......) where . is the total number of requests. Our approach is based on a dynamic program that keeps track of the number of pending requests in each of .(log.) line segments that are geometrically increasing in length.
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Offline Sorting Buffers on LineOn a line metric with . uniformly spaced points, our algorithm yields the first . and runs in quasi-polynomial time .(......) where . is the total number of requests. Our approach is based on a dynamic program that keeps track of the number of pending requests in each of .(log.) line segments that are geometrically increasing in length.
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