Online Optimization with Uncertain Information

  title={Online Optimization with Uncertain Information},
  author={Mohammad Mahdian and Hamid Nazerzadeh and Amin Saberi},
  journal={ACM Trans. Algorithms},
We introduce a new framework for designing online algorithms that can incorporate additional information about the input sequence, while maintaining a reasonable competitive ratio if the additional information is incorrect. Within this framework, we present online algorithms for several problems including allocation of online advertisement space, load balancing, and facility location. 
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