A polynomial-time algorithm to find the shortest cycle basis of a graph
SIAM Journal on Computing
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SFCS '91 Proceedings of the 32nd annual symposium on Foundations of computer science
Journal of the ACM (JACM)
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SIAM Journal on Computing
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SIAM Journal on Computing
Journal of Algorithms
STOC '01 Proceedings of the thirty-third annual ACM symposium on Theory of computing
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Journal of the ACM (JACM)
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SODA '04 Proceedings of the fifteenth annual ACM-SIAM symposium on Discrete algorithms
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Journal of Algorithms - Special issue: Twelfth annual ACM-SIAM symposium on discrete algorithms
Extremal Graph Theory
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STACS'07 Proceedings of the 24th annual conference on Theoretical aspects of computer science
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IPCO'05 Proceedings of the 11th international conference on Integer Programming and Combinatorial Optimization
Finding the smallest H-Subgraph in real weighted graphs and related problems
ICALP'06 Proceedings of the 33rd international conference on Automata, Languages and Programming - Volume Part I
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STACS'05 Proceedings of the 22nd annual conference on Theoretical Aspects of Computer Science
Finding, counting and listing all triangles in large graphs, an experimental study
WEA'05 Proceedings of the 4th international conference on Experimental and Efficient Algorithms
Faster approximation of distances in graphs
WADS'07 Proceedings of the 10th international conference on Algorithms and Data Structures
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We describe a simple combinatorial approximation algorithm for finding a shortest (simple) cycle in an undirected graph. For an undirected graph G of unknown girth k, our algorithm returns with high probability a cycle of length at most 2k for even k and 2k + 2 for odd k, in time O(n3/2 √log n). Thus, in general, it yields a 2 2/3 approximation. We study also the problem of finding a simple cycle of minimum total weight in an undirected graph with nonnegative edge weights. We present a simple combinatorial 2-approximation algorithm for a minimum weight (simple) cycle in an undirected graph with nonnegative integer edge weights in the range {1, 2, ..., M}. This algorithm runs in time O(n2 log n log M).