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CORR
2008
Springer
110views Education» more  CORR 2008»
14 years 9 months ago
Finding Dense Subgraphs in G(n,1/2)
Finding the largest clique in random graphs is a well known hard problem. It is known that a random graph G(n, 1/2) almost surely has a clique of size about 2 log n. A simple greed...
Atish Das Sarma, Amit Deshpande, Ravi Kannan
APPROX
2008
Springer
184views Algorithms» more  APPROX 2008»
14 years 11 months ago
Approximately Counting Embeddings into Random Graphs
Let H be a graph, and let CH(G) be the number of (subgraph isomorphic) copies of H contained in a graph G. We investigate the fundamental problem of estimating CH(G). Previous res...
Martin Fürer, Shiva Prasad Kasiviswanathan
GLOBECOM
2008
IEEE
15 years 4 months ago
A Memory-Optimized Bloom Filter Using an Additional Hashing Function
— A Bloom filter is a simple space-efficient randomized data structure for the representation set of items in order to support membership queries. In recent years, Bloom filte...
Mahmood Ahmadi, Stephan Wong
STOC
2000
ACM
112views Algorithms» more  STOC 2000»
15 years 1 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
RSA
2011
102views more  RSA 2011»
14 years 4 months ago
Dependent random choice
: We describe a simple and yet surprisingly powerful probabilistic technique which shows how to find in a dense graph a large subset of vertices in which all (or almost all) small...
Jacob Fox, Benny Sudakov