Bayesian Regression Markets
| Autor: | Falconer, Thomas, Kazempour, Jalal, Pinson, Pierre |
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| Rok vydání: | 2023 |
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| Druh dokumentu: | Working Paper |
| Popis: | 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. Comment: 35 pages, 11 figures, 3 tables. Published in Journal of Machine Learning Research (2024) |
| Databáze: | arXiv |
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