Optimal Online Data Sampling or How to Hire the Best Secretaries

@article{Girdhar2009OptimalOD,
  title={Optimal Online Data Sampling or How to Hire the Best Secretaries},
  author={Yogesh A. Girdhar and Gregory Dudek},
  journal={2009 Canadian Conference on Computer and Robot Vision},
  year={2009},
  pages={292-298}
}
  • Yogesh A. Girdhar, G. Dudek
  • Published 25 May 2009
  • Computer Science, Mathematics
  • 2009 Canadian Conference on Computer and Robot Vision
The problem of online sampling of data, can be seen as a generalization of the classical secretary problem. The goal is to maximize the probability of picking the k highest scoring samples in our data, making the decision to select or reject a sample on-line. We present a new and simple on-line algorithm to optimally make this selection. We then apply this algorithm to a sequence of images taken by a mobile robot, with the goal of identifying the most interesting and informative images. 
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