Spectral partitioning of random graphs

Annual Symposium on Foundations of Computer Science - Proceedings

Volumn , Issue , 2001, Pages 529-537

  McSherry, F ^a  

^a University of Washington   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMPUTATIONAL COMPLEXITY; MATHEMATICAL MODELS; MATRIX ALGEBRA; PROBABILITY DISTRIBUTIONS; PROBLEM SOLVING; RANDOM PROCESSES;

RANDOM GRAPHS;

GRAPH THEORY;

EID: 0035186726     PISSN: 02725428     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/sfcs.2001.959929     Document Type: Conference Paper

References (22)

1. Fast computation of low rank matrix approximations
2. A spectral technique for coloring random 3-colorable graphs
3. Finding a large hidden clique in a random graph
4. Data mining through spectral analysis
5. Coloring random and semi-random k-colorable graphs
6. Eigenvalues and graph bisection: An average-case analysis
7. Graph bisection algorithms with good average case behaviour
8. Algorithms for graph partitioning on the planted partition model
9. The rotation of eigenvectors by a perturbation 3
10. Fast solution of some random NP-hard problems
11. Heuristics for finding large independent sets, with applications to coloring semirandom graphs
12. The eigenvalues of random symmetric matrices
13. Simulated annealing for graph bisection
14. On clusterings: Good, bad and spectral
15. The probabilistic analysis of some combinatorial search algorithms
16. On the concentration of eigenvalues of random symmetric matrices
17. Expected behaviour of graph colouring algorithms
18. Expected complexity of graph partitioning problems
19. Spectral partitioning works: Planar graphs and finite element meshes
20. Almost all k-colorable graphs are easy to color