Correlation Clustering: Maximizing Agreements via Semidefinite Programming

Proceedings of the Annual ACM-SIAM Symposium on Discrete Algorithms

Volumn 15, Issue , 2004, Pages 519-520

  Swamy, Chaitanya ^a  

^a Department of Obstetrics Gynecology   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CORRELATION CLUSTERING PROBLEM; SEMIDEFINITE PROGRAMMING;

ALGORITHMS; APPROXIMATION THEORY; CONSTRAINT THEORY; CORRELATION METHODS; FUNCTIONS; MATHEMATICAL PROGRAMMING; PROBLEM SOLVING; RANDOM PROCESSES;

GRAPH THEORY;

EID: 1842435182     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (7)

1. G. Andersson, I. Engebretsen, and J. Håstad. A new approach to use semidefinite programming with applications to linear equations mod p. J. Algorithms, 39:162-204, 2001.
2. N. Bansal, A. Blum, and S. Chawla. Correlation clustering. Proc. 43rd IEEE FOCS, 238-217, 2002.
3. M. Charikar, V. Guruswami and A. Wirth. Clustering with qualitative information. To appear in Proc. 44th IEEE FOCS, 2003.
4. E. Demaine and N. Immorlica. Correlation clustering with partial information. Proc. 6th APPROX, 1-13, 2003.
5. D. Emanuel and A. Fiat. Correlation clustering - minimizing disagreements on arbitrary weighted graphs. Proc. 11th ESA, 208-220, 2003.
6. A. Frieze and M. Jerrurn. Improved approximation algorithms for MAX k-CUT and MAX-BISECTION. Algorithmica, 18:67-81, 1997.
7. M. Goemans and D. Williamson. Improved approximation algorithms for maximum cut and satisfiability problems using semidefinite programming. JACM, 42:1115-1145, 1995.