Interpretability, Then What? Editing Machine Learning Models to Reflect Human Knowledge and Values - researchr publication authors

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Zijie J. Wang, Alex Kale, Harsha Nori, Peter Stella, Mark E. Nunnally, Duen Horng Chau, Mihaela Vorvoreanu, Jennifer Wortman Vaughan, Rich Caruana 0001. Interpretability, Then What? Editing Machine Learning Models to Reflect Human Knowledge and Values. In Aidong Zhang, Huzefa Rangwala, editors, KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14 - 18, 2022. pages 4132-4142, ACM, 2022. [doi]

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