Differentiable and Scalable Generative Adversarial Models for Data Imputation (Extended Abstract)-Reference-Cited by-同舟云学术

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Differentiable and Scalable Generative Adversarial Models for Data Imputation (Extended Abstract)

Published:2024-05-13 Issue: Volume: Page:5739-5740
ISSN:
Container-title:2024 IEEE 40th International Conference on Data Engineering (ICDE)
language:
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Author:

Wu Yangyang¹,Wang Jun²,Miao Xiaoye³,Wang Wenjia⁴,Yin Jianwei⁵

Affiliation:

1. Software College, Zhejiang University,Ningbo,China

2. Academy of Interdisciplinary Studies, The Hong Kong University of Science and Technology,Hong Kong,China

3. Center for Data Science, Zhejiang University,Hangzhou,China

4. Information Hub, The Hong Kong University of Science and Technology (Guangzhou),Guangzhou,China

5. College of Computer Science, Zhejiang University,Hangzhou,China

Funder

National Key R&D Program of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10597630/10597390/10597926.pdf?arnumber=10597926

Reference2 articles.

1. Differentiable and Scalable Generative Adversarial Models for Data Imputation

2. Efficient and effective data imputation with influence functions

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