On the Distortion Value of the Elections with Abstention
Authors: Mohammad Ghodsi, Mohamad Latifian, Masoud Seddighin1981-1988
AAAI 2019 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | Our results fully characterize the distortion value and provide a rather complete picture of the model. In Theorem 3.1 we state the main result of this section. The basic idea to prove Theorem 3.1 is as follows: we prove that for every election E, there exists an election instance E with the same expected winner, and D(E ) D(E). In Lemmas 3.3,3.4, and 3.5 we introduce three sorts of valid displacement which help us collect the voters. |
| Researcher Affiliation | Academia | Mohammad Ghodsi, Mohamad Latifian, Masoud Seddighin Sharif University of Technology, Institute for Research in Fundamental Sciences (IPM) School of CS ghodsi@sharif.edu, {latifian, mseddighin}@ce.sharif.edu |
| Pseudocode | No | The paper does not contain any sections explicitly labeled 'Pseudocode' or 'Algorithm', nor does it present structured code-like procedures. |
| Open Source Code | No | The paper does not provide any explicit statements about releasing source code for the described methodology, nor does it include links to a code repository. |
| Open Datasets | No | The paper is theoretical and does not conduct experiments on a specific dataset. Therefore, it does not refer to a publicly available dataset with concrete access information. |
| Dataset Splits | No | The paper is theoretical and does not involve empirical experiments with datasets, thus it does not specify training, validation, or test dataset splits. |
| Hardware Specification | No | The paper is theoretical and focuses on mathematical analysis and proofs, thus it does not mention specific hardware specifications used for experiments. |
| Software Dependencies | No | The paper is theoretical and does not describe computational experiments or software implementations, so it does not list any specific software dependencies with version numbers. |
| Experiment Setup | No | The paper is theoretical and focuses on mathematical models and proofs. It does not describe an empirical experimental setup with hyperparameters or system-level training settings. |