Shapley value-based data valuation for machine learning data markets

2025 article gvalue2025datamarkets ○ Not yet verified

Venue

Discover Applied Sciences

Abstract

Proposes G-Value to bridge the gap between leave-one-out (LOO) and Shapley value approaches for data valuation. Addresses practical applications in machine learning data markets.

BibTeX

Local Entry

@article{gvalue2025datamarkets,
  title = {Shapley value-based data valuation for machine learning data markets},
  year = {2025},
  journal = {Discover Applied Sciences},
  url = {https://link.springer.com/article/10.1007/s42452-025-07328-z},
  abstract = {Proposes G-Value to bridge the gap between leave-one-out (LOO) and Shapley value approaches for data valuation. Addresses practical applications in machine learning data markets.}
}

From AUTO:OPENALEX

@article{gvalue2025datamarkets,
  title = {Shapley value-based data valuation for machine learning data markets},
  author = {Carlos Soares},
  year = {2025},
  journal = {Discover Applied Sciences},
  doi = {10.1007/s42452-025-07328-z}
}