Post-processing of Differentially Private Data: A Fairness Perspective
Authors: Keyu Zhu, Ferdinando Fioretto, Pascal Van Hentenryck
IJCAI 2022 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | The theoretical analysis is complemented with numerical simulations on Census data. |
| Researcher Affiliation | Academia | 1Georgia Institute of Technology 2Syracuse University |
| Pseudocode | No | The paper does not contain structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide concrete access to source code for the methodology described. There are no repository links or explicit code release statements. |
| Open Datasets | No | The paper mentions using 'US Census data' and '2010 US census release' but does not provide concrete access information (specific link, DOI, repository name, or formal citation with authors/year) for the specific dataset instances used in their simulations, nor does it refer to an established benchmark dataset with explicit access details. |
| Dataset Splits | No | The paper does not provide specific dataset split information (exact percentages, sample counts, citations to predefined splits, or detailed splitting methodology) needed to reproduce the data partitioning. |
| Hardware Specification | No | The paper does not provide specific hardware details (exact GPU/CPU models, processor types with speeds, memory amounts, or detailed computer specifications) used for running its experiments. |
| Software Dependencies | No | The paper does not provide specific ancillary software details, such as library or solver names with version numbers, needed to replicate the experiment. |
| Experiment Setup | Yes | The experiments use the Laplace mechanism with parameter λ 10 and the Gaussian mechanism with parameter σ 25. The empirical studies of α-fairness and its bounds in Theorem 1 associated with the post-processing mechanism πS over 1, 000, 000 independent runs are reported in Table 1. |