Guyanqi/Awesome-Privacy
Repository for collection of research papers on privacy.
This collection helps researchers and practitioners explore cutting-edge techniques for protecting sensitive data in machine learning and data analysis. It provides access to a curated list of research papers on privacy-enhancing technologies like Differential Privacy. If you're working on data analysis or machine learning and need to understand or implement methods to safeguard information, this resource compiles relevant academic literature.
344 stars. No commits in the last 6 months.
Use this if you are a researcher or data scientist needing to understand the theoretical foundations and practical applications of privacy-preserving techniques in data analysis and machine learning.
Not ideal if you are looking for ready-to-use software libraries or practical implementation guides rather than academic research papers.
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GPL-3.0
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Jul 19, 2024
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