Computing Pareto Optimal Committees
Authors: Haris Aziz, Jérôme Lang, Jérôme Monnot
IJCAI 2016 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | For each of the notions, we undertake a detailed study of complexity of computing and verifying Pareto optimal outcomes. Table 1 summarizes the complexity results. |
| Researcher Affiliation | Collaboration | Haris Aziz NICTA and UNSW Sydney, Australia haris.aziz@data61.csiro.au J erˆome Lang and J erˆome Monnot LAMSADE, Universit e Paris-Dauphine Paris, France {lang, jerome.monnot}@lamsade.dauphine.fr |
| Pseudocode | Yes | Algorithm 1: Committee Voting Serial Dictatorship |
| Open Source Code | No | The paper does not provide concrete access to source code for the methodology described. |
| Open Datasets | No | The paper is theoretical and does not involve experiments with datasets. |
| Dataset Splits | No | The paper is theoretical and does not describe experiments that would require dataset splits. |
| Hardware Specification | No | The paper is theoretical and does not describe any specific hardware used for experiments. |
| Software Dependencies | No | The paper is theoretical and does not mention specific software dependencies with version numbers. |
| Experiment Setup | No | The paper is theoretical and does not describe an experimental setup with hyperparameters or training settings. |