Online Stochastic Weighted Matching: Improved Approximation Algorithms

@inproceedings{Haeupler2011OnlineSW,
  title={Online Stochastic Weighted Matching: Improved Approximation Algorithms},
  author={Bernhard Haeupler and Vahab S. Mirrokni and Morteza Zadimoghaddam},
  booktitle={WINE},
  year={2011}
}
Motivated by the display ad allocation problem on the Internet, we study the online stochastic weighted matching problem. In this problem, given an edge-weighted bipartite graph, nodes of one side arrive online i.i.d. according to a known probability distribution. Recently, a sequence of results by Feldman et. al [14] and Manshadi et. al [20] result in a 0.702-approximation algorithm for the unweighted version of this problem, aka online stochastic matching, breaking the 1−1 / e barrier. Those… 

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