Ye-D/PPML-Resource
Materials about Privacy-Preserving Machine Learning
This resource provides a curated list of academic papers focused on privacy-preserving machine learning. It helps researchers and practitioners stay current with the latest advancements by providing an organized collection of relevant publications. The output is a categorized list of papers, useful for anyone working with sensitive data and machine learning.
263 stars.
Use this if you are a researcher or practitioner in machine learning who needs to find and track academic papers on methods to protect privacy while training or deploying models.
Not ideal if you are looking for code implementations, tutorials, or a general introduction to machine learning concepts.
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Feb 02, 2026
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