Sample Complexity of Posted Pricing for a Single Item

Selling a single item to n self-interested buyers is a fundamental problem in economics, where the two objectives typically considered are welfare maximization and revenue maximization. Since the optimal mechanisms are often impractical and do not work for sequential buyers, posted pricing mechanisms, where fixed prices are set for the item for different buyers, have emerged as a practical and effective alternative. This paper investigates how many samples are needed from buyers’ value distributions to find near-optimal posted prices, considering both independent and correlated buyer distributions, and welfare versus revenue maximization. We obtain matching upper and lower bounds (up to logarithmic factors) on the sample complexity for all these settings.

  • Published in:
    NeurIPS 2024 spotlight
  • Type:
    Inproceedings
  • Authors:
    Jin, Billy; Kesselheim, Thomas; Ma, Will; Singla, Sahil
  • Year:
    2024

Citation information

Jin, Billy; Kesselheim, Thomas; Ma, Will; Singla, Sahil: Sample Complexity of Posted Pricing for a Single Item, NeurIPS 2024 spotlight, 2024, https://neurips.cc/virtual/2024/poster/96043, Jin.etal.2024b,

Associated Lamarr Researchers

lamarr institute person Kesselheim Thomas - Lamarr Institute for Machine Learning (ML) and Artificial Intelligence (AI)

Prof. Dr. Thomas Kesselheim

Principal Investigator Resource-aware ML to the profile