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    • 10th SmartData@PoliTO Workshop – Present and Future Directions
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      • Empowering Data Owners with Control in Outsourcing and Sharing Scenarios
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    • PhD Course: Topological Data Analysis
    • PhD Course: Data Science for Networks
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Home » Publications » Learning Confidence Intervals for Feature Importance: A Fast Shapley-based Approach

Learning Confidence Intervals for Feature Importance: A Fast Shapley-based Approach

Davide Napolitano, Lorenzo Vaiani, Luca Cagliero (2023) Learning Confidence Intervals for Feature Importance: A Fast Shapley-based Approach, In: Proceedings of 7th International workshop on Data Analytics solutions for Real-LIfe APplications

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