A Quantum Algorithm for Shapley Value Estimation

Fuente: arXiv
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Hauptverfasser: Burge, Iain, Barbeau, Michel, Garcia-Alfaro, Joaquin
Format: Preprint
Veröffentlicht: 2023
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author Burge, Iain
Barbeau, Michel
Garcia-Alfaro, Joaquin
author_facet Burge, Iain
Barbeau, Michel
Garcia-Alfaro, Joaquin
contents In the classical context, the cooperative game theory concept of the Shapley value has been adapted for post hoc explanations of machine learning models. However, this approach does not easily translate to eXplainable Quantum ML (XQML). Finding Shapley values can be highly computationally complex. We propose quantum algorithms which can extract Shapley values within some confidence interval. Our results perform in polynomial time. We demonstrate the validity of each approach under specific examples of cooperative voting games.
format Preprint
id arxiv_https___arxiv_org_abs_2301_04727
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle A Quantum Algorithm for Shapley Value Estimation
Burge, Iain
Barbeau, Michel
Garcia-Alfaro, Joaquin
Emerging Technologies
Cryptography and Security
Quantum Algebra
In the classical context, the cooperative game theory concept of the Shapley value has been adapted for post hoc explanations of machine learning models. However, this approach does not easily translate to eXplainable Quantum ML (XQML). Finding Shapley values can be highly computationally complex. We propose quantum algorithms which can extract Shapley values within some confidence interval. Our results perform in polynomial time. We demonstrate the validity of each approach under specific examples of cooperative voting games.
title A Quantum Algorithm for Shapley Value Estimation
topic Emerging Technologies
Cryptography and Security
Quantum Algebra
url https://arxiv.org/abs/2301.04727