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ICML
2006
IEEE
16 years 4 months ago
Graph model selection using maximum likelihood
In recent years, there has been a proliferation of theoretical graph models, e.g., preferential attachment and small-world models, motivated by real-world graphs such as the Inter...
Adam Kalai, Ivona Bezáková, Rahul Sa...
CVPR
2008
IEEE
16 years 6 months ago
From skeletons to bone graphs: Medial abstraction for object recognition
letons to Bone Graphs: Medial Abstraction for Object Recognition Diego Macrini University of Toronto Kaleem Siddiqi McGill University Sven Dickinson University of Toronto Medial d...
Diego Macrini, Kaleem Siddiqi, Sven J. Dickinson
ESA
2004
Springer
120views Algorithms» more  ESA 2004»
15 years 9 months ago
Maximum Matchings in Planar Graphs via Gaussian Elimination
We present a randomized algorithm for finding maximum matchings in planar graphs in time O(nω/2 ), where ω is the exponent of the best known matrix multiplication algorithm. Sin...
Marcin Mucha, Piotr Sankowski
ENTCS
2006
151views more  ENTCS 2006»
15 years 4 months ago
Extending C for Checking Shape Safety
The project Safe Pointers by Graph Transformation at the University of York has developed a method for specifying the shape of pointer-data structures by graph reduction, and a st...
Mike Dodds, Detlef Plump
APPROX
2004
Springer
179views Algorithms» more  APPROX 2004»
15 years 9 months ago
Maximum Weight Independent Sets and Matchings in Sparse Random Graphs. Exact Results Using the Local Weak Convergence Method
ABSTRACT: Let G(n, c/n) and Gr(n) be an n-node sparse random graph and a sparse random rregular graph, respectively, and let I(n, r) and I(n, c) be the sizes of the largest indepen...
David Gamarnik, Tomasz Nowicki, Grzegorz Swirszcz