Bayesian Regression Markets

Thomas Falconer, Jalal Kazempour, Pierre Pinson
10/23/2023
cs.LG

Official code: tdfalc/regression-markets (5 stars, last commit 2025-08-10).

Abstract

Although machine learning tasks are highly sensitive to the quality of input data, relevant datasets can often be challenging for firms to acquire, especially when held privately by a variety of owners. For instance, if these owners are competitors in a downstream market, they may be reluctant to share information. Focusing on supervised learning for regression tasks, we develop a regression market to provide a monetary incentive for data sharing. Our mechanism adopts a Bayesian framework, allowing us to consider a more general class of regression tasks. We present a thorough exploration of the market properties, and show that similar proposals in literature expose the market agents to sizeable financial risks, which can be mitigated in our setup.

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Code Implementations(1)

tdfalc/regression-marketsOfficial
50PythonJul 21, 20231 years ago

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Cite this paper

@article{falconer2023bayesian,
  title  = {Bayesian Regression Markets},
  author = {Thomas Falconer and Jalal Kazempour and Pierre Pinson},
  year   = {2023},
  eprint = {2310.14992},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2310.14992v3}
}

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