Exactly Minimax-Optimal Locally Differentially Private Sampling
Authors: Hyun-Young Park, Shahab Asoodeh, Si-Hyeon Lee
NeurIPS 2024 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Our numerical experiments demonstrate the superiority of our mechanisms over baselines, in terms of theoretical utilities for finite data space and of empirical utilities for continuous data space. |
| Researcher Affiliation | Academia | Hyun-Young Park School of Electrical Engineering KAIST phy811@kaist.ac.kr Shahab Asoodeh Department of Computing and Software Mc Master University asoodeh@mcmaster.ca Si-Hyeon Lee School of Electrical Engineering KAIST sihyeon@kaist.ac.kr |
| Pseudocode | No | The paper does not contain structured pseudocode or algorithm blocks. |
| Open Source Code | Yes | All codes for experiments and figures are attached as a supplementary material, and can be found at the online repository1. The instructions to reproduce the results in the paper are in Appendix H. 1https://github.com/phy811/Optimal-LDP-Sampling. |
| Open Datasets | No | The paper describes generating synthetic data for its experiments: "We randomly construct N Gaussian mixture distributions P1, P2, ..., PN ∈ P, where each Pj is generated independently according to some rules specified in Appendix F.2." It does not use or provide access to a pre-existing publicly available dataset for training. |
| Dataset Splits | No | The paper does not explicitly mention the use of a validation dataset split in its experimental setup. |
| Hardware Specification | Yes | All experiments are performed on our simulation PC with the following specifications: OS: Ubuntu 22.04.1 CPU: Intel(R) Core(TM) i9-9900X Memory: 64GB |
| Software Dependencies | No | The paper mentions using Python and notes that the baseline used Julia, but it does not specify version numbers for Python, Julia, or any specific libraries (e.g., PyTorch, NumPy) used in the implementation within the main text or appendices. It mentions an 'environment.yaml' file in supplementary material, but the specific versions are not listed in the paper itself. |
| Experiment Setup | Yes | In the experiment in the paper, we use k0 = 2 and δ1 = δ2 = 10-5. For the baseline mechanism, we use MBDE with the same hyperparameter setup as [35, Section 5]. |