tutorial

Applications and Computation of the Shapley Value in Databases and Machine Learning

Authors:

Jian PeiAuthors Info & Claims

SIGMOD/PODS '24: Companion of the 2024 International Conference on Management of Data

Pages 630 - 635

https://doi.org/10.1145/3626246.3654680

Published: 09 June 2024 Publication History

Abstract

Recently, the Shapley value, a concept rooted in cooperative game theory, has found more and more applications in databases and machine learning. Due to its combinatoric nature, the computation of the Shapley value is #P-hard. To address this challenge, numerous studies are actively engaged in developing efficient computation methods or exploring alternative solutions in specific application contexts. Applications of the Shapley value in databases and machine learning as well as fast computation or approximation of the Shapley value in those applications are becoming a new research frontier in the database community. This tutorial presents a comprehensive and systematic overview of Shapley value applications and computation within both database and machine learning domains. We survey the existing methods from a unique perspective that diverges from the current literature. Unlike most reviews, which mainly focus on applications, our approach focuses on the underlying algorithmic mechanisms and application specific assumptions in these methods. This approach allows us to highlight the similarities and differences among the various Shapley value applications and computation techniques more effectively. Our tutorial categorizes these methods based on their intrinsic processes, cutting across different applications. The tutorial begins with an introduction to the Shapley value and its diverse applications in databases and machine learning. Subsequently, it delves into the computational challenges of the Shapley value, presents cutting-edge solutions for its efficient computation, and explores alternative solutions.

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Cited By

Pang JPei JXia HLi XLiu J(2025)Shapley Value Estimation based on Differential MatrixProceedings of the ACM on Management of Data10.1145/37097253:1(1-28)Online publication date: 11-Feb-2025
https://dl.acm.org/doi/10.1145/3709725
Kemgne MNjionou BKwuida LIgnatov D(2024)Shapley Values in Classification Problems with Triadic Formal Concept AnalysisConceptual Knowledge Structures10.1007/978-3-031-67868-4_6(83-96)Online publication date: 9-Sep-2024
https://dl.acm.org/doi/10.1007/978-3-031-67868-4_6

Index Terms

Applications and Computation of the Shapley Value in Databases and Machine Learning
1. Computing methodologies
  1. Machine learning
2. Information systems
  1. Data management systems

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cover image ACM Conferences

SIGMOD/PODS '24: Companion of the 2024 International Conference on Management of Data

June 2024

694 pages

ISBN:9798400704222

DOI:10.1145/3626246

General Chairs:
Pablo Barcelo
Universidad Catolica, Chile
,
Nayat Sanchez-Pi
INRIA Chile
,
Program Chairs:
Alexandra Meliou
University of Massachusetts Amherst, USA
,
S. Sudarshan
Indian Institute of Technology Bombay

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Published: 09 June 2024

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Beyond the Horizon Grant by Duke University

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SIGMOD/PODS '24: International Conference on Management of Data

June 9 - 15, 2024

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Cited By

Pang JPei JXia HLi XLiu J(2025)Shapley Value Estimation based on Differential MatrixProceedings of the ACM on Management of Data10.1145/37097253:1(1-28)Online publication date: 11-Feb-2025
https://dl.acm.org/doi/10.1145/3709725
Kemgne MNjionou BKwuida LIgnatov D(2024)Shapley Values in Classification Problems with Triadic Formal Concept AnalysisConceptual Knowledge Structures10.1007/978-3-031-67868-4_6(83-96)Online publication date: 9-Sep-2024
https://dl.acm.org/doi/10.1007/978-3-031-67868-4_6

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