Bayesian Regression Markets

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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 distributed amongst 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 proposed 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.
Original languageEnglish
JournalJournal of Machine Learning Research
Volume25
Number of pages35
ISSN1533-7928
Publication statusPublished - 2024

Keywords

  • Regression
  • Bayesian interface
  • Collaborative analytics
  • Data markets
  • Game theory

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