Differentially private stochastic gradient descent with low-noise-Reference-Cited by-同舟云学术

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Differentially private stochastic gradient descent with low-noise

Published:2024-06 Issue: Volume:585 Page:127557
ISSN:0925-2312
Container-title:Neurocomputing
language:en
Short-container-title:Neurocomputing

Author:

Wang Puyu^ORCID,Lei Yunwen,Ying Yiming^ORCID,Zhou Ding-Xuan^ORCID

Funder

National Natural Science Foundation of China

Research Grants Council, University Grants Committee

University of Sydney

City University of Hong Kong

National Science Foundation

Publisher

Elsevier BV

Reference51 articles.

1. Efficient online and batch learning using forward backward splitting;Duchi;J. Mach. Learn. Res.,2009

2. Deep Learning;Goodfellow,2016

3. On the convergence of stochastic gradient descent with adaptive stepsizes;Li,2019

4. Learning overparameterized neural networks via stochastic gradient descent on structured data;Li,2018

5. Optimal rates for multi-pass stochastic gradient methods;Lin;J. Mach. Learn. Res.,2017

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1. A dynamic anonymization privacy-preserving model based on hierarchical sequential three-way decisions;Information Sciences;2025-01

2. Privacy-Preserving Frank-Wolfe on Shuffle Model;Acta Mathematicae Applicatae Sinica, English Series;2024-06-01

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