Summary of Bayesian Frequency Estimation Under Local Differential Privacy with An Adaptive Randomized Response Mechanism, by Soner Aydin and Sinan Yildirim
Bayesian Frequency Estimation Under Local Differential Privacy With an Adaptive Randomized Response Mechanism
by Soner Aydin, Sinan Yildirim
First submitted to arxiv on: 11 May 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Cryptography and Security (cs.CR); Machine Learning (stat.ML)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary Frequency estimation is crucial for many applications involving personal data, such as user behavior and preferences. As data are often collected sequentially, estimating the distribution of categorical data online while preserving privacy is vital. The proposed AdOBEst-LDP algorithm enhances the utility of future privatized categorical data by leveraging inference from previously collected privatized data. This adaptive LDP mechanism constrains output to a subset of categories predicting the next user’s data. Bayesian estimation improves the utility of future privatized data, utilizing posterior sampling through stochastic gradient Langevin dynamics, an efficient approximate Markov chain Monte Carlo method. The algorithm is evaluated using various information metrics, including the Fisher information matrix, total variation distance, and information entropy. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Imagine trying to understand what people like or dislike without invading their privacy. This paper shows how to do just that by guessing the distribution of categorical data (like favorite colors or music genres) while keeping that data private. The idea is to use previous data to make better guesses about future data, all while protecting users’ privacy. The algorithm uses a special way of collecting and processing data to make it more accurate and reliable. |
Keywords
» Artificial intelligence » Inference
