Holistic Explainability Requirements for End-to-End Machine Learning in IoT Cloud Systems-Reference-Cited by-同舟云学术

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Holistic Explainability Requirements for End-to-End Machine Learning in IoT Cloud Systems

Published:2021-09 Issue: Volume: Page:
ISSN:
Container-title:2021 IEEE 29th International Requirements Engineering Conference Workshops (REW)
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Author:

Nguyen My-Linh,Phung Thao,Ly Duong-Hai,Truong Hong-Linh

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9581322/9582276/09582347.pdf?arnumber=9582347

Cited by 7 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Candidate Solutions for Defining Explainability Requirements of AI Systems;Lecture Notes in Computer Science;2024

2. Requirements on and Procurement of Explainable Algorithms—A Systematic Review of the Literature;Advances in Intelligent Systems and Computing;2024

3. Requirements engineering for artificial intelligence systems: A systematic mapping study;Information and Software Technology;2023-06

4. Transductive Semi-Supervised Metric Network for Reject Inference in Credit Scoring;IEEE Transactions on Computational Social Systems;2023

5. Constructive Interpretability with CoLabel: Corroborative Integration, Complementary Features, and Collaborative Learning;2022 IEEE 4th International Conference on Cognitive Machine Intelligence (CogMI);2022-12

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