forked from 626_privacy/tensorflow_privacy
32 lines
811 B
Markdown
32 lines
811 B
Markdown
# Project Title
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Faster Differentially Private Convex Optimization via Second-Order Methods
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https://arxiv.org/abs/2112.03570 <br>
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by Arun Ganesh, Mahdi Haghifam, Thomas Steinke, Abhradeep Thakurta.
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## Description
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Implementation of the optimizatoin algorithms proposed in
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https://arxiv.org/abs/2112.03570 <br>
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## Getting Started
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You will need to install fairly standard dependencies
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run 'run_privacy_utility' to compare the convergence speed and excess loss of
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different algorithms.
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### Citation
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You can cite this paper with
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```
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@article{ganesh2023faster,
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title={Faster Differentially Private Convex Optimization
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via Second-Order Methods},
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author={Ganesh, Arun and Haghifam, Mahdi and Steinke, Thomas
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and Thakurta, Abhradeep},
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journal={arXiv preprint arXiv:2305.13209},
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year={2023}
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}
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```
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