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APPROX
2007
Springer
100views Algorithms» more  APPROX 2007»
13 years 11 months ago
Implementing Huge Sparse Random Graphs
Consider a scenario where one desires to simulate the execution of some graph algorithm on random input graphs of huge, perhaps even exponential size. Sampling and storing these h...
Moni Naor, Asaf Nussboim
AIRS
2006
Springer
13 years 9 months ago
Natural Document Clustering by Clique Percolation in Random Graphs
Document clustering techniques mostly depend on models that impose explicit and/or implicit priori assumptions as to the number, size, disjunction characteristics of clusters, and/...
Wei Gao, Kam-Fai Wong
STOC
2000
ACM
112views Algorithms» more  STOC 2000»
13 years 9 months ago
A random graph model for massive graphs
We propose a random graph model which is a special case of sparse random graphs with given degree sequences. This model involves only a small number of parameters, called logsize ...
William Aiello, Fan R. K. Chung, Linyuan Lu
IPPS
2010
IEEE
13 years 3 months ago
A distributed diffusive heuristic for clustering a virtual P2P supercomputer
Abstract--For the management of a virtual P2P supercomputer one is interested in subgroups of processors that can communicate with each other efficiently. The task of finding these...
Joachim Gehweiler, Henning Meyerhenke
JACM
2010
111views more  JACM 2010»
13 years 3 months ago
Finding a maximum matching in a sparse random graph in O(n) expected time
We present a linear expected time algorithm for finding maximum cardinality matchings in sparse random graphs. This is optimal and improves on previous results by a logarithmic f...
Prasad Chebolu, Alan M. Frieze, Páll Melste...