Online Stochastic Matching: New Algorithms with Better Bounds

Online Stochastic Matching: New Algorithms with Better Bounds

We consider variants of the online stochastic bipartite matching problem motivated by Internet advertising display applications, as introduced in Feldman et al. [Feldman J, Mehta A, Mirrokni VS, Muthukrishnan S (2009) Online stochastic matching: Beating 1 − 1/e. FOCS '09: Proc. 50th Annual IEEE...

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Bibliographic Details
Main Authors: Jaillet, Patrick (Contributor), Lu, Xin (Contributor)
Other Authors: Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor), Massachusetts Institute of Technology. Laboratory for Information and Decision Systems (Contributor), Massachusetts Institute of Technology. Operations Research Center (Contributor)
Format: Article
Language:English
Published: Institute for Operations Research and the Management Sciences (INFORMS), 2015-12-21T14:35:28Z.
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