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Titlebook: Approximation and Online Algorithms; 10th International W Thomas Erlebach,Giuseppe Persiano Conference proceedings 2013 Springer-Verlag Ber

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Probabilistic ,-Median Clustering in Data Streamsed probabilistic input points, .. is the minimum weight of a probabilistic input point, .. is the minimum realization probability, and . is the error probability of the construction. We show how to maintain our coreset for Euclidean spaces in data streams.
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Black and White Bin Packingform very well — and for all online algorithms we also prove the universal . bound . which significantly exceeds the known . bound 1.58889 on classical online bin packing. We also design an online algorithm which is 3-competitive in the absolute sense. A 2.5-approximation algorithm and an APTAS is also given for the offline version.
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Conference proceedings 2013vited talk were carefully reviewed and selected from 60 submissions. The workshop covered areas such as geometric problems, online algorithms, scheduling, algorithmic game theory, and approximation algorithms.
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,Erzeugung und Anwendung von Röntgenblitzen,ower bound of Ω(log(./.)/loglog(./.)) on the competitive ratio of finding a maximum independent set in bipartite graphs if no knowledge of the underlying graph is available and if the advice is of size .. We complement the lower bounds by providing corresponding upper bounds.
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O. Haxel,J. H. D. Jensen,H. E. Suesswith neighborhoods (.) problem, and the maximum weight version (.) has not been studied previously to our knowledge. We provide deterministic and parameterized approximation algorithms for the . problem, and a parameterized algorithm for the . problem. Additionally, we present hardness of approximation proofs for both settings.
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Ergebnisse der Exakten Naturwissenschaftene first prove a . factor, where . depends on a partition of the jobs according to their heat contributions. Next, we refine our partition and provide a linear program that shows a lower bound of 0.72 on the approximation factor.
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https://doi.org/10.1007/978-3-642-94299-0olynomial algorithms for fixed parameter values, as well as several . results. The parameters under consideration are the treewidth of the input graph, the sizes . and . and the vertex load, i.e. the maximum number of paths passing through any vertex.
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