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Hierarchical Hub Labelings for Shortest Paths
 PROCEEDINGS OF THE 20TH ANNUAL EUROPEAN SYMPOSIUM ON ALGORITHMS (ESA’12), VOLUME 7501 OF LECTURE NOTES IN COMPUTER SCIENCE
, 2012
"... We study hierarchical hub labelings for computing shortest paths. Our new theoretical insights into the structure of hierarchical labels lead to faster preprocessing algorithms, making the labeling approach practical for a wider class of graphs. We also find smaller labels for road networks, impro ..."
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Cited by 20 (10 self)
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We study hierarchical hub labelings for computing shortest paths. Our new theoretical insights into the structure of hierarchical labels lead to faster preprocessing algorithms, making the labeling approach practical for a wider class of graphs. We also find smaller labels for road networks, improving the query speed.
Fast local search for the maximum independent set problem
 In Proceedings of Workshop on Experimental Algorithms, LNCS 5038
, 2008
"... Abstract. Given a graph G = (V, E), the independent set problem is that of finding a maximumcardinality subset S of V such that no two vertices in S are adjacent. We present a fast local search routine for this problem. Our algorithm can determine in linear time if a maximal solution can be improve ..."
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Cited by 13 (1 self)
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Abstract. Given a graph G = (V, E), the independent set problem is that of finding a maximumcardinality subset S of V such that no two vertices in S are adjacent. We present a fast local search routine for this problem. Our algorithm can determine in linear time if a maximal solution can be improved by replacing a single vertex with two others. We also show that an incremental version of this method can be useful within more elaborate heuristics. We test our algorithms on instances from the literature as well as on new ones proposed in this paper. 1.
Exact Combinatorial BranchandBound for Graph Bisection
"... We present a novel exact algorithm for the minimum graph bisection problem, whose goal is to partition a graph into two equallysized cells while minimizing the number of edges between them. Our algorithm is based on the branchandbound framework and, unlike most previous approaches, it is fully co ..."
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Cited by 7 (3 self)
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We present a novel exact algorithm for the minimum graph bisection problem, whose goal is to partition a graph into two equallysized cells while minimizing the number of edges between them. Our algorithm is based on the branchandbound framework and, unlike most previous approaches, it is fully combinatorial. We present stronger lower bounds, improved branching rules, and a new decomposition technique that contracts entire regions of the graph without losing optimality guarantees. In practice, our algorithm works particularly well on instances with relatively small minimum bisections, solving large realworld graphs (with tens of thousands to millions of vertices) to optimality.
R.F.: Better bounds for graph bisection
 In: Proc. European Symposium on Algorithms (ESA
, 2012
"... Abstract. We introduce new lower bounds for the minimum graph bisection problem. Within a branchandbound framework, they enable the solution of a wide variety of instances with tens of thousands of vertices to optimality. Our algorithm compares favorably with the best previous approaches, solving ..."
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Cited by 6 (2 self)
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Abstract. We introduce new lower bounds for the minimum graph bisection problem. Within a branchandbound framework, they enable the solution of a wide variety of instances with tens of thousands of vertices to optimality. Our algorithm compares favorably with the best previous approaches, solving longstanding open instances in minutes. 1
Hub labels: Theory and practice
 In SEA
, 2014
"... Abstract. The Hub Labeling algorithm (HL) is an exact shortest path algorithm with excellent query performance on some classes of problems. It precomputes some auxiliary information (stored as a label) for each vertex, and its query performance depends only on the label size. While there are polynom ..."
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Cited by 4 (0 self)
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Abstract. The Hub Labeling algorithm (HL) is an exact shortest path algorithm with excellent query performance on some classes of problems. It precomputes some auxiliary information (stored as a label) for each vertex, and its query performance depends only on the label size. While there are polynomialtime approximation algorithms to find labels of approximately optimal size, practical solutions use hierarchical hub labels (HHL), which are faster to compute but offer no guarantee on the label size. We improve the theoretical and practical performance of the HL approximation algorithms, enabling us to compute such labels for moderately large problems. Our comparison shows that HHL algorithms scale much better and find labels that usually are not much bigger than the theoretically justified HL labels. 1
Computing Classic Closeness Centrality, at Scale
, 2014
"... Closeness centrality, first considered by Bavelas (1948), is an importance measure of a node in a network which is based on the distances from the node to all other nodes. The classic definition, proposed by Bavelas (1950), Beauchamp (1965), and Sabidussi (1966), is (the inverse of) the average dist ..."
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Closeness centrality, first considered by Bavelas (1948), is an importance measure of a node in a network which is based on the distances from the node to all other nodes. The classic definition, proposed by Bavelas (1950), Beauchamp (1965), and Sabidussi (1966), is (the inverse of) the average distance to all other nodes. We propose the first highly scalable (near lineartime processing and linear space overhead) algorithm for estimating, within a small relative error, the classic closeness centralities of all nodes in the graph. Our algorithm applies to undirected graphs, as well as for centrality computed with respect to roundtrip distances in directed graphs. For directed graphs, we also propose an efficient algorithm that approximates generalizations of classic closeness centrality to outbound and inbound centralities. Although it does not provide worstcase theoretical approximation guarantees, it is designed to perform well on real networks. We perform extensive experiments on large networks, demonstrating high scalability and accuracy. 1
Supervisors:
, 2014
"... anderen, als die angegebenen Quellen und Hilfsmittel benutzt, die wörtlich oder ..."
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anderen, als die angegebenen Quellen und Hilfsmittel benutzt, die wörtlich oder
Math. Program., Ser. A manuscript No. (will be inserted by the editor) An Exact Combinatorial Algorithm for Minimum Graph Bisection
"... Abstract We present a novel exact algorithm for the minimum graph bisection problem, whose goal is to partition a graph into two equallysized cells while minimizing the number of edges between them. Our algorithm is based on the branchandbound framework and, unlike most previous approaches, it is ..."
Abstract
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Abstract We present a novel exact algorithm for the minimum graph bisection problem, whose goal is to partition a graph into two equallysized cells while minimizing the number of edges between them. Our algorithm is based on the branchandbound framework and, unlike most previous approaches, it is fully combinatorial. We introduce novel lower bounds based on packing trees, as well as a new decomposition technique that contracts entire regions of the graph while preserving optimality guarantees. Our algorithm works particularly well on graphs with relatively small minimum bisections, solving to optimality several large realworld instances (with up to millions of vertices) for the first time.
3.2 Output File Formats.......................................... 4
"... This paper serves as a user guide to the framework KaMIS (Karlsruhe Maximum Independent Sets). The framwork computes high quality independent sets in huge sparse graphs. We give a rough overview of the techniques used within the framework and describe the user interface as well as the file formats u ..."
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This paper serves as a user guide to the framework KaMIS (Karlsruhe Maximum Independent Sets). The framwork computes high quality independent sets in huge sparse graphs. We give a rough overview of the techniques used within the framework and describe the user interface as well as the file formats used.