Differentially Private Federated Continual Learning with Heterogeneous Cohort Privacy-Reference-Cited by-同舟云学术

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Differentially Private Federated Continual Learning with Heterogeneous Cohort Privacy

Published:2022-12-17 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE International Conference on Big Data (Big Data)
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Author:

Chathoth Ajesh Koyatan¹,Necciai Clark P¹,Jagannatha Abhyuday²,Lee Stephen¹

Affiliation:

1. University of Pittsburgh,Pittsburgh,PA,USA

2. University of Massachusetts Amherst,Amherst,MA,USA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10020192/10020156/10021082.pdf?arnumber=10021082

Reference30 articles.

1. The secret sharer: Measuring unintended neural network memorization & extracting secrets;carlini,2018

2. Privacy-preserving deep learning;shokri;Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security,2015

3. Heterogeneous differential privacy;alaggan,2015

4. R\’enyi differential privacy of the sampled gaussian mechanism;mironov,2019

5. Differentially private continual learning;farquhar,2019

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. Differentially Private Federated Learning with Heterogeneous Group Privacy;2023 IEEE International Conferences on Internet of Things (iThings) and IEEE Green Computing & Communications (GreenCom) and IEEE Cyber, Physical & Social Computing (CPSCom) and IEEE Smart Data (SmartData) and IEEE Congress on Cybermatics (Cybermatics);2023-12-17

2. A DQN-Based Multi-Objective Participant Selection for Efficient Federated Learning;Future Internet;2023-06-08

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