Equitable Stable Matchings in Quadratic Time
Authors: Nikolaos Tziavelis, Ioannis Giannakopoulos, Katerina Doka, Nectarios Koziris, Panagiotis Karras
NeurIPS 2019 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Our experimental study with simulated markets shows that DLS outperforms the state of the art in equity measures and matches the most efficient ones in runtime. |
| Researcher Affiliation | Academia | Nikolaos Tziavelis Northeastern University Ioannis Giannakopoulos NTU Athens Katerina Doka NTU Athens Nectarios Koziris NTU Athens Panagiotis Karras Aarhus University |
| Pseudocode | Yes | Algorithm 1 Power Balance |
| Open Source Code | Yes | Code and data are available at https://github.com/ntzia/stable-marriage |
| Open Datasets | Yes | We use synthetic datasets that draw preferences from three distributions: Uniform(U), Discrete(D), and Gaussian(G)... Last, we apply our solution on real data... Code and data are available at https://github.com/ntzia/stable-marriage |
| Dataset Splits | No | The paper mentions using 'synthetic datasets' and 'real data' but does not specify explicit train/validation/test splits, percentages, or sample counts for these datasets. |
| Hardware Specification | Yes | The algorithms are implemented in Java4 and tested on an Intel Xeon 2.67GHz CPU with 28GB RAM. |
| Software Dependencies | No | The paper states 'The algorithms are implemented in Java4' but does not provide specific Java versions or other software dependencies with version numbers. |
| Experiment Setup | Yes | We set the probability parameter in BILS to 0, in i BILS to 0.125, the limit parameter of POWERBALANCE to n log2 2 n/10 , and the parameters in HMS to k = 2 log n and m = log n . |