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A simple parallel algorithm for the maximal independent set problem
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Property testing and its connection to learning and approximation
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Distributed computing: a locality-sensitive approach
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SALSA: the stochastic approach for link-structure analysis
ACM Transactions on Information Systems (TOIS)
Approximation algorithms for maximization problems arising in graph partitioning
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Robust Characterizations of Polynomials withApplications to Program Testing
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Massive Quasi-Clique Detection
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Three theorems regarding testing graph properties
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Proceedings of the thirty-seventh annual ACM symposium on Theory of computing
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Tolerant property testing and distance approximation
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Theoretical Computer Science
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Proceedings of the nineteenth annual ACM-SIAM symposium on Discrete algorithms
Constant-Time Approximation Algorithms via Local Improvements
FOCS '08 Proceedings of the 2008 49th Annual IEEE Symposium on Foundations of Computer Science
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Given an undirected graph and 0 ≤ Ɛ ≤ = 1, a set of nodes is called Ɛ-near clique if all but an Ɛ fraction of the pairs of nodes in the set have a link between them. In this paper we present a fast synchronous network algorithm that uses small messages and finds a nearclique. Specifically, we present a constant-time algorithm that finds, with constant probability of success, a linear size Ɛ-near clique if there exists an Ɛ3-near clique of linear size in the graph. The algorithm uses messages of O(log n) bits. The failure probability can be reduced to n-Ω(1) in O(log n) time factor, and the algorithm also works if the graph contains a clique of size Ω(n/logα log n) for some α ∈ (0, 1). Our approach is based on a new idea of adapting property testing algorithms to the distributed setting.