Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Spectral Techniques in Graph Algorithms
LATIN '98 Proceedings of the Third Latin American Symposium on Theoretical Informatics
Smoothed analysis of algorithms: Why the simplex algorithm usually takes polynomial time
Journal of the ACM (JACM)
Approximating Maximum Clique by Removing Subgraphs
SIAM Journal on Discrete Mathematics
Recognizing More Unsatisfiable Random k-SAT Instances Efficiently
SIAM Journal on Computing
Spectral norm of random matrices
Combinatorica
Smoothed analysis: an attempt to explain the behavior of algorithms in practice
Communications of the ACM - A View of Parallel Computing
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For the maximum independent set problem, strong inapproximability bounds for worst-case efficient algorithms exist. We give a deterministic algorithm beating these bounds, with polynomial expected running-time for semi-random graphs: an adversary chooses a graph with n vertices, and then edges are flipped with a probability of @e. Our algorithm guarantees an approximation ratio of O(n@e) for sufficiently large @e.