The diameter of randomly perturbed digraphs and some applications

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3122, Issue , 2004, Pages 345-356

  Flaxman, Abraham D ^a   Frieze, Alan M ^a  

^a CARNEGIE MELLON UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; APPROXIMATION ALGORITHMS; COMBINATORIAL OPTIMIZATION; COMPUTATION THEORY; DIRECTED GRAPHS; OPTIMIZATION; POLYNOMIAL APPROXIMATION; PROBABILITY;

CENTRAL OBSERVATIONS; COMPUTATIONAL TASK; HIGH PROBABILITY; LOG-SPACE ALGORITHMS; POLYNOMIAL-TIME ALGORITHMS; SMOOTHED ANALYSIS; STRONGLY CONNECTED; VERTEX DISJOINT PATHS;

GRAPH THEORY;

EID: 34248364134     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-27821-4_31     Document Type: Article

References (29)

1. R. Aleliunas, R. M. Karp, R. J. Lipton, L. Lovász, and C. RackofF, Random walks, traversal sequences, and the complexity of maze problems, Proc. 20th IEEE Symp. on the Foundations of Computer Science (1979), 218-223.
2. N. Alon, A. Gyárfás, and M. Ruszinkó, Decreasing the diameter of bounded degree graphs, J. Graph Theory 35 (2000), 161-172.
3. N. Alon and N. Kahale, A spectral technique for coloring random 3-colorable graphs, DIMACS TR-94-35, 1994.
4. C. Banderier, K. Mehlhorn, and R. Beier. Smoothed analysis of three combinatorial problems, Proc. 28th Intl. Symp. on the Mathematical Foundations of Computer Science (2003).
5. R. Beier and B. Vöcking, Typical properties of winners and losers in discrete optimization, to appear in STOC04 (2004).
6. A. Blum and J. Spencer, Coloring Random and Semi-Random k-Colorable Graphs, Journal of Algorithms 19 (1995) 204-234.
7. T. Bohman, A.M. Frieze and R. Martin, How many random edges make a dense graph Hamiltonian? Random Structures and Algorithms 22 (2003) 33-42.
8. T. Bohman, A.M. Frieze, M. Krivelevich and R. Martin, Adding random edges to dense graphs, Random Structures and Algorithms 24 (2004) 105-117.
9. B. Bollobás, Random Graphs, Second Edition, Cambridge University Press (2001)
10. B. Bollobás and F. Chung, The Diameter of a Cycle Plus a Random Matching, SIAM Journal on Discrete Mathematics 1(3) (1988) 328-333.
11. L. Bechetti, S. Leonardi, A. Marchetti-Spaccamela, G. Schaefer, and T. Vredeveld, Smoothening Helps: A probabilistic analysis of the multi-level feedback algorithm, FOCS03 (2003).
12. F. Chung and M. Garey, Diameter bounds for altered graphs, Journal of Graph Theory 8, (1984) 511-534.
13. C. Cooper and A. M. Frieze, The size of the largest strongly connected component of a random digraph with a given degree sequence Combinatorics, Probability and Computing 13 (2004) 319-338.
14. M. Faloutsos, P. Faloutsos and C. Faloutsos, On powerlaw relationships of the Internet topology, SIGCOMM 99 (1999) 251-262.
15. U. Feige and R. Krauthgamer, Finding and certifying a large hidden clique in a semirandom graph, Random Structures and Algorithms, 16:2 (2000) 195-208.
16. U. Feige and J. Kilian, Heuristics for Semirandom Graph Problems, Journal of Computer and System Sciences 63 (2001) 639-671.
17. U. Feige, A Tight Upper Bound on the Cover Time for Random Walks on Graphs, Random Structures and Algorithms 6 (1995) 51-54.
18. O. Goldreich, S. Goldwasser, D. Ron, Property testing and its connection to learning and approximation, J. ACM 45 (1998) 653-750.
19. O. Goldreich, D. Ron, Property testing in bounded degree graphs, Proc. 29th STOC (1997) 406-415.
20. S. Janson, T. Łuczak and A. Ruciński, Random graphs, Wiley-Interscience (2000).
21. N. D. Jones, Space-bounded reducibility among combinatorial problems, Journal of Computer and System Sciences 11 (1975) 68-75.
22. R. Karp, The transitive closure of a random digraph, Random Structures and Algorithms 1 (1990) 73-94.
23. M. Krivelevich and P. Tetali, personal communication.
24. N. Nisan, On read-once vs. multiple access randomness in logspace, Theoretical Computer Science 107:1 (1993) 135-144.
25. M. Santha and U. Vazirani, Generating quasi-random sequences from semi-random sources, Journal of Computer and System Sciences 33 (1986) 75-87.
26. M. Sipser, Introduction to the Theory of Computation, PWS (1996).
27. D. Spielman and S.H. Teng, Smoothed Analysis of Algorithms: Why The Simplex Algorithm Usually Takes Polynomial Time, Proc. of the The Thirty-Third Annual ACM Symposium on Theory of Computing, (2001) 296-305.
28. D. Spielman and S.H. Teng, Smoothed Analysis: Motivation and Discrete Models, Proc. of WADS 2003, Lecture Notes in Computer Science, Springer-Verlag (2003).
29. H. Vollmer and K.W. Wagner, Measure one results in computational complexity theory, Advances in Algorithms, Languages, and Complexity (1997) 285-312.