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A decision-theoretic generalization of on-line learning and an application to boosting
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STACS'99 Proceedings of the 16th annual conference on Theoretical aspects of computer science
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Linear programming in the semi-streaming model with application to the maximum matching problem
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Finding graph matchings in data streams
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Linear programming in the semi-streaming model with application to the maximum matching problem
ICALP'11 Proceedings of the 38th international conference on Automata, languages and programming - Volume Part II
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Proceedings of the twenty-third annual ACM-SIAM symposium on Discrete Algorithms
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In this paper, we study linear programming based approaches to the maximum matching problem in the semi-streaming model. The semi-streaming model has gained attention as a model for processing massive graphs as the importance of such graphs has increased. This is a model where edges are streamed-in in an adversarial order and we are allowed a space proportional to the number of vertices in a graph. In recent years, there has been several new results in this semistreaming model. However broad techniques such as linear programming have not been adapted to this model. We present several techniques to adapt and optimize linear programming based approaches in the semistreaming model with an application to the maximum matching problem. As a consequence, we improve (almost) all previous results on this problem, and also prove new results on interesting variants.