# Making the Most of Your Samples

@article{Huang2015MakingTM, title={Making the Most of Your Samples}, author={Zhiyi Huang and Y. Mansour and T. Roughgarden}, journal={Proceedings of the Sixteenth ACM Conference on Economics and Computation}, year={2015} }

We study the problem of setting a price for a potential buyer with a valuation drawn from an unknown distribution D. The seller has "data" about D in the form of m ≥ 1 i.i.d. samples, and the algorithmic challenge is to use these samples to obtain expected revenue as close as possible to what could be achieved with advance knowledge of D. Our first set of results quantifies the number of samples m that are necessary and sufficient to obtain a (1-ε)-approximation. For example, for an unknown… Expand

#### 75 Citations

Learning Multi-Item Auctions with (or without) Samples

- Mathematics, Computer Science
- 2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS)
- 2017

Robust Revenue Maximization Under Minimal Statistical Information

- Computer Science, Mathematics
- WINE
- 2020

Sample-driven optimal stopping: From the secretary problem to the i.i.d. prophet inequality

- Mathematics, Computer Science
- ArXiv
- 2020

#### References

SHOWING 1-2 OF 2 REFERENCES