Semantic Scholar Open Access 2022 329 sitasi

The Shapley Value in Machine Learning

Benedek Rozemberczki Lauren Watson P. Bayer Hao-Tsung Yang Oliver Kiss +2 lainnya

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Abstrak

Over the last few years, the Shapley value, a solution concept from cooperative game theory, has found numerous applications in machine learning. In this paper, we first discuss fundamental concepts of cooperative game theory and axiomatic properties of the Shapley value. Then we give an overview of the most important applications of the Shapley value in machine learning: feature selection, explainability, multi-agent reinforcement learning, ensemble pruning, and data valuation. We examine the most crucial limitations of the Shapley value and point out directions for future research.

Topik & Kata Kunci

Computer Science

Penulis (7)

Benedek Rozemberczki

Lauren Watson

P. Bayer

Hao-Tsung Yang

Oliver Kiss

Sebastian Nilsson

Rik Sarkar

Format Sitasi

APA MLA BibTeX

Rozemberczki, B., Watson, L., Bayer, P., Yang, H., Kiss, O., Nilsson, S. et al. (2022). The Shapley Value in Machine Learning. https://doi.org/10.24963/ijcai.2022/778

Akses Cepat

Lihat di Sumber doi.org/10.24963/ijcai.2022/778

Informasi Jurnal

Tahun Terbit: 2022
Bahasa: en
Total Sitasi: 329×
Sumber Database: Semantic Scholar
DOI: 10.24963/ijcai.2022/778
Akses: Open Access ✓