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» Sampling from large graphs
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SIAMSC
2008
182views more  SIAMSC 2008»
14 years 11 months ago
A Distributed SDP Approach for Large-Scale Noisy Anchor-Free Graph Realization with Applications to Molecular Conformation
We propose a distributed algorithm for solving Euclidean metric realization problems arising from large 3D graphs, using only noisy distance information, and without any prior kno...
Pratik Biswas, Kim-Chuan Toh, Yinyu Ye
UAI
2000
15 years 1 months ago
Adaptive Importance Sampling for Estimation in Structured Domains
Sampling is an important tool for estimating large, complex sums and integrals over highdimensional spaces. For instance, importance sampling has been used as an alternative to ex...
Luis E. Ortiz, Leslie Pack Kaelbling
ICCTA
2007
IEEE
15 years 3 months ago
What Graphs can be Efficiently Represented by BDDs?
We have carried out experimental research into implicit representation of large graphs using reduced ordered binary decision diagrams (OBDDs). We experimentally show that for grap...
Changxing Dong, Paul Molitor
ICPR
2008
IEEE
15 years 6 months ago
Pattern vectors from the Ihara zeta function
This paper shows how to construct pattern vectors from the Ihara zeta function for the purposes of characterizing graph structures. To avoid the risk of sampling the meaningless i...
Peng Ren, Richard C. Wilson, Edwin R. Hancock
RSA
2002
51views more  RSA 2002»
14 years 11 months ago
Testing subgraphs in large graphs
Let H be a fixed graph with h vertices, let G be a graph on n vertices and suppose that at least n2 edges have to be deleted from it to make it H-free. It is known that in this ca...
Noga Alon