Test Score Algorithms for Budgeted Stochastic Utility Maximization

@article{Lee2020TestSA,
  title={Test Score Algorithms for Budgeted Stochastic Utility Maximization},
  author={Dabeen Lee and Milan Vojnovi{\'c} and Seyoung Yun},
  journal={ArXiv},
  year={2020},
  volume={abs/2012.15194}
}
Motivated by recent developments in designing algorithms based on individual item scores for solving utility maximization problems, we study the framework of using test scores, defined as a statistic of observed individual item performance data, for solving the budgeted stochastic utility maximization problem. We extend an existing scoring mechanism, namely, the replication test scores, to incorporate heterogeneous item costs as well as item values. We show that a natural greedy algorithm that… 

Sketching stochastic valuation functions

The problem of sketching a stochastic valuation function is considered as the expectation of a valuation function of independent random item values, and it is shown that for monotone subadditive or submodular valuation functions that satisfy a weak homogeneity condition, or certain other conditions, there exist discretized distributions of item values that yield a sketch valuation function which is a constant-factor approximation.

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