Differentially Private Ensemble Classifiers for Data Streams-Reference-Cited by-同舟云学术

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Differentially Private Ensemble Classifiers for Data Streams

Published:2022-02-11 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining
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Author:

Gondara Lovedeep¹,Wang Ke¹,Silva Carvalho Ricardo¹

Affiliation:

1. Simon Fraser University, Burnaby, BC, Canada

Funder

Natural Sciences and Engineering Research Council of Canada

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3488560.3498498

Reference45 articles.

1. Deep Learning with Differential Privacy

2. AndroZoo

3. H. S. Anderson and P. Roth . 2018 . EMBER: An Open Dataset for Training Static PE Malware Machine Learning Models . ArXiv e-prints (April 2018). arxiv: 1804.04637 [cs.CR] H. S. Anderson and P. Roth. 2018. EMBER: An Open Dataset for Training Static PE Malware Machine Learning Models . ArXiv e-prints (April 2018). arxiv: 1804.04637 [cs.CR]

4. Differentially Private Bayesian Programming

5. The Balanced Accuracy and Its Posterior Distribution

Cited by 2 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. Unraveling Privacy Risks of Individual Fairness in Graph Neural Networks;2024 IEEE 40th International Conference on Data Engineering (ICDE);2024-05-13

2. Privacy-preserving data (stream) mining techniques and their impact on data mining accuracy: a systematic literature review;Artificial Intelligence Review;2023-02-22

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