Fair Sequential Selection Using Supervised Learning Models
Authors: Mohammad Mahdi Khalili, Xueru Zhang, Mahed Abroshan
NeurIPS 2021 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | The experiments on real-world datasets validate the theoretical results. |
| Researcher Affiliation | Academia | Mohammad Mahdi Khalili CIS Department University of Delaware Newark, DE, USA khalili@udel.edu Xueru Zhang CSE Department Ohio State University Columbus, OH, USA zhang.12807@osu.edu Mahed Abroshan Alan Turing Institute London, UK mabroshan@turing.ac.uk |
| Pseudocode | No | The paper describes algorithms using mathematical formulations and text, but does not provide structured pseudocode or algorithm blocks. |
| Open Source Code | Yes | The codes are available here. |
| Open Datasets | Yes | FICO credit score dataset [41]. Adult income dataset [42]. |
| Dataset Splits | No | The paper mentions sample sizes and uses pre-trained models but does not explicitly specify train/validation/test splits, percentages, or absolute counts for dataset partitioning. |
| Hardware Specification | No | The paper does not provide specific hardware details (e.g., GPU/CPU models, memory) used for running the experiments. |
| Software Dependencies | No | We first train a logistic regression classifier (using sklearn package and default parameters) as the pretrained model. The paper mentions 'sklearn package' but does not specify a version number for it or any other software dependency. |
| Experiment Setup | Yes | We consider a common method where the decisions are made based on a threshold rule, i.e., selecting an applicant if its qualification score R = r(X, A) is above a threshold τ. ... the optimal thresholds τ0, τ1 in Table 1 are close to the maximum score 100, especially under EO and SP fairness notions. ... we add the following time constraint to optimization (13): the probability that no applicant is selected after 100 time steps should be less than 1. |