Online submodular maximization: beating 1/2 made simple

  title={Online submodular maximization: beating 1/2 made simple},
  author={Niv Buchbinder and Moran Feldman and Mohit Garg},
  journal={Mathematical Programming},
The Submodular Welfare Maximization problem (SWM) captures an important subclass of combinatorial auctions and has been studied extensively. In particular, it has been studied in a natural online setting in which items arrive one-by-one and should be allocated irrevocably upon arrival. For this setting, Korula et al. (SIAM J Comput 47(3):1056–1086, 2018) were able to show that the greedy algorithm is 0.5052-competitive when the items arrive in a uniformly random order. Unfortunately, however… 

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