This study by Likun Qin and Tianshuo Qiu provides an in-depth analysis of Local Differential Privacy (LDP) and its applications in machine learning. LDP alters user data locally before it’s…
Continue readingThe paper presents an algorithm that relaxes the Differential Privacy (DP) guarantee of a randomized response gradually. The output from each relaxation maintains the same probability distribution as a standard…
Continue readingThe article discusses the issue of privacy in graph embedding, a powerful tool for learning latent representations for nodes in a graph. The authors highlight the need for privacy-preserving graph…
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