mlsanityData to 14 Oct 2026

Towards Efficient Data Valuation Based on the Shapley Value

arXiv 1902.10275 ↗First posted 27 Feb 2019cs.LG stat.MLcited by 281

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Abstract (arXiv)

"How much is my data worth?" is an increasingly common question posed by organizations and individuals alike. An answer to this question could allow, for instance, fairly distributing profits among multiple data contributors and determining prospective compensation when data breaches happen. In this paper, we study the problem of data valuation by utilizing the Shapley value, a popular notion of value which originated in cooperative game theory. The Shapley value defines a unique payoff scheme that satisfies many desiderata for the notion of data value. However, the Shapley value often requires exponential time to compute. To meet this challenge, we propose a repertoire of efficient algorithms for approximating the Shapley value. We also demonstrate the value of each training instance for various benchmark datasets.

Key facts. Cited by 281 papers in the map (data through 14 Oct 2026). First posted on arXiv 27 Feb 2019.

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Citing papers per year: 2021: 32; 2022: 33; 2023: 50; 2024: 61; 2025: 61; 2026: 44.

281 papers.

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  1. 2021Understanding Dataset Difficulty with V-Usable Informationcited by 291
  2. 2023TRAK: Attributing Model Behavior at Scalecited by 283
  3. 2022Datamodels: Predicting Predictions from Training Datacited by 189
  4. 2021Beta Shapley: a Unified and Noise-reduced Data Valuation Framework for Machine Learningcited by 165
  5. 2022Training Data Influence Analysis and Estimation: A Surveycited by 135
  6. 2022Data Banzhaf: A Robust Data Valuation Framework for Machine Learningcited by 132
  7. 2023Foundation Models and Fair Usecited by 116
  8. 2022The Shapley Value in Machine Learningcited by 98
  9. 2024What is Your Data Worth to GPT? LLM-Scale Data Valuation with Influence Functionscited by 94
  10. 2022DataPerf: Benchmarks for Data-Centric AI Developmentcited by 90
  11. 2024Data Shapley in One Training Runcited by 81
  12. 2021GTG-Shapley: Efficient and Accurate Participant Contribution Evaluation in Federated Learningcited by 74
38 more
  1. 2022Faith-Shap: The Faithful Shapley Interaction Indexcited by 69
  2. 2023LAVA: Data Valuation without Pre-Specified Learning Algorithmscited by 69
  3. 2021Towards Fairness-Aware Federated Learningcited by 58
  4. 2023Fair Federated Medical Image Segmentation via Client Contribution Estimationcited by 52
  5. 2023SHAP-IQ: Unified Approximation of any-order Shapley Interactionscited by 51
  6. 2022Measuring the Effect of Training Data on Deep Learning Predictions via Randomized Experimentscited by 50
  7. 2023Synthetic Datasets for Autonomous Driving: A Surveycited by 48
  8. 2021Incentive Mechanisms for Federated Learning: From Economic and Game Theoretic Perspectivecited by 47
  9. 2023Evaluating Data Attribution for Text-to-Image Modelscited by 45
  10. 2023The Journey, Not the Destination: How Data Guides Diffusion Modelscited by 43
  11. 2021One for One, or All for All: Equilibria and Optimality of Collaboration in Federated Learningcited by 39
  12. 2022Mechanisms that Incentivize Data Sharing in Federated Learningcited by 39
  13. 2021HYDRA: Hypergradient Data Relevance Analysis for Interpreting Deep Neural Networkscited by 38
  14. 2021A Comprehensive Survey of Incentive Mechanism for Federated Learningcited by 38
  15. 2023Data-OOB: Out-of-bag Estimate as a Simple and Efficient Data Valuecited by 38
  16. 2022First is Better Than Last for Language Data Influencecited by 34
  17. 2024Training Data Attribution via Approximate Unrolled Differentiationcited by 34
  18. 2022CS-Shapley: Class-wise Shapley Values for Data Valuation in Classificationcited by 32
  19. 2024Most Influential Subset Selection: Challenges, Promises, and Beyondcited by 32
  20. 2021DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregationcited by 31
  21. 2024Rethinking Data Shapley for Data Selection Tasks: Misleads and Meritscited by 29
  22. 2024Unleashing the Power of Data Tsunami: A Comprehensive Survey on Data Assessment and Selection for Instruction Tuning of Language Modelscited by 29
  23. 2021Data Shapley Valuation for Efficient Batch Active Learningcited by 27
  24. 2022Repairing Neural Networks by Leaving the Right Past Behindcited by 27
  25. 2021SHAQ: Incorporating Shapley Value Theory into Multi-Agent Q-Learningcited by 26
  26. 2021The Shapley Value of Classifiers in Ensemble Gamescited by 23
  27. 2022Shapley-NAS: Discovering Operation Contribution for Neural Architecture Searchcited by 23
  28. 2022Understanding Influence Functions and Datamodels via Harmonic Analysiscited by 23
  29. 2024Provably Accurate Shapley Value Estimation via Leverage Score Samplingcited by 23
  30. 2021Improving Fairness for Data Valuation in Horizontal Federated Learningcited by 22
  31. 2024Data Attribution for Text-to-Image Models by Unlearning Synthesized Imagescited by 22
  32. 2024Permissive Information-Flow Analysis for Large Language Modelscited by 22
  33. 2024Diffusion Attribution Score: Evaluating Training Data Influence in Diffusion Modelscited by 22
  34. 2023Data Selection for Fine-tuning Large Language Models Using Transferred Shapley Valuescited by 21
  35. 2024Stochastic Amortization: A Unified Approach to Accelerate Feature and Data Attributioncited by 21
  36. 2021Incentivizing Collaboration in Machine Learning via Synthetic Data Rewardscited by 20
  37. 2022Fundamentals of Task-Agnostic Data Valuationcited by 19
  38. 2023Threshold KNN-Shapley: A Linear-Time and Privacy-Friendly Approach to Data Valuationcited by 19

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