A number of papers on differential privacy, fairness and reproducibility. This is a tentative list:
1. Legal and general papers:
- Broken Promises of Privacy: Responding to the Surprising Failure of Anonymization, Ohm, 2009.
- Big Data's Disparate Impact. Barocas and Selbst, 2016.
- Robust De-anonymization of Large Sparse Datasets. Narayanan and Shmatikov.
- A Survey Technique for Eliminating Evasive Answer Bias, Warner, 1965.
2. Differential privacy
- Calibrating noise to sensitivity in private data analysis]].(Approximate DP: See also
https://github.com/frankmcsherry/blog/blob/master/posts/2017-02-08.md )
- The staircase mechanism in differential privacy. Geng et al. 2015.
- Renyi Differential Privacy. Mironov, 2017.
- Distributed Differential Privacy via Shuffling. Cheu et al, 2019.
- Federated Naive Bayes under Differential Privacy.]] Marchioro et al.
- Resolving Individuals Contributing Trace Amounts of DNA to Highly Complex Mixtures Using High-Density SNP Genotyping Microarrays
- Needles in the Haystack: Identifying Individuals Present in Pooled Genomic Data]], Braun et al. 2009.
- Privacy Preserving GWAS Data Sharing. Uhlerop et al. 2013.
- A New Analysis of Differential Privacy’s Generalization Guarantees, Jung et al. 2019.
3. Fairness
- Fair prediction with disparate impact: A study of bias in recidivism prediction instruments, Chouldechova, 2017.
- Inherent Trade-Offs in the Fair Determination of Risk Scores]], Kleinberg et al. 2016.
- Meritocratic Fairness for Cross-Population Selection, Kearns et al. 2017.
- Fairness through awareness, Dwork et al. 2011.
