Robust Rent Division
Authors: Dominik Peters, Ariel D. Procaccia, David Zhu
NeurIPS 2022 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We end with some experiments on data taken from Spliddit. They suggest that our three new rules significantly outperform the Spliddit maximin rule on robustness metrics. |
| Researcher Affiliation | Academia | Dominik Peters CNRS, Université Paris Dauphine PSL dominik@lamsade.fr Ariel D. Procaccia Harvard University arielpro@seas.harvard.edu David Zhu Harvard University david.zhu@gmail.com |
| Pseudocode | No | The paper describes algorithms but does not include structured pseudocode or algorithm blocks. |
| Open Source Code | Yes | Did you include the code, data, and instructions needed to reproduce the main experimental results (either in the supplemental material or as a URL)? [Yes] In the supplemental material, but not including the data. |
| Open Datasets | No | We evaluated our rules on user data taken from Spliddit. This dataset was kindly provided to us in anonymized form by the maintainer of Spliddit, Nisarg Shah. ... We use a proprietary dataset from Spliddit.org, whose creators we cite [Goldman and Procaccia, 2014]. |
| Dataset Splits | No | The paper describes drawing samples and evaluating performance on them but does not specify a distinct 'validation' split or percentage for model training as typically understood in machine learning. |
| Hardware Specification | Yes | Figure 3 shows average computation time to compute allocations optimizing EFrate S and envy S, using Gurobi 9.1.2 on four threads of an AMD Ryzen 2990WX (128 GB RAM). |
| Software Dependencies | Yes | Figure 3 shows average computation time to compute allocations optimizing EFrate S and envy S, using Gurobi 9.1.2 on four threads of an AMD Ryzen 2990WX (128 GB RAM). |
| Experiment Setup | Yes | For each noise model and choice of ", we produced a sample S of size m = 100. We then computed allocations maximizing EFrate S and minimizing envy S. |