Provenance-based Explanations for Machine Learning (ML) Models-Reference-Cited by-同舟云学术

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Provenance-based Explanations for Machine Learning (ML) Models

Published:2023-04 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE 39th International Conference on Data Engineering Workshops (ICDEW)
language:
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Author:

Turnau Justin¹,Akwari Nkechi¹,Lee Seokki¹,Rajput Dwarkesh¹

Affiliation:

1. University of Cincinnati

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10148090/10148105/10148106.pdf?arnumber=10148106

Reference13 articles.

1. The many shapley values for model explanation;sundararajan;International Conference on Machine Learning,2020

2. 17. A Value for n-Person Games

3. Pug: a framework and practical implementation for why and why-not provenance;lee;VLDB J,2018

4. Formal semantics and high performance in declarative machine learning using Datalog

5. Understanding black-box predictions via influence functions;koh;ICML,2017

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