Differentially Private Multi-Label Learning Is Harder Than You'd Think
Author:
Affiliation:
1. Leipzig University Center for Scalable Data Analytics and Artificial Intelligence (ScaDS. AI),Dept. of Computer Science,Dresden/Leipzig,Germany
2. Center for Scalable Data Analytics and Artificial, Intelligence (ScaDS. AI),Dresden/Leipzig,Germany
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10628447/10628451/10628452.pdf?arnumber=10628452
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1. Reliability of Supervised Machine Learning Using Synthetic Data in Health Care: Model to Preserve Privacy for Data Sharing
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3. Comparison of Deep Learning Approaches for Multi-Label Chest X-Ray Classification
4. The secret sharer: Evaluating and testing unintended memorization in neural networks;Carlini,2019
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