Condorcet Relaxation In Spatial Voting
Authors: Arnold Filtser, Omrit Filtser5407-5414
AAAI 2021 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | In this paper, we show that 0.557 ≤ β (Rd, 2) for any dimension d (notice that 1/d < 0.557 for any d ≥ 4). In addition, we prove that for every metric space (X, d) it holds that √2 − 1 ≤ β (X,d), and show that there exists a metric space for which β (X,d) = 1/2. |
| Researcher Affiliation | Academia | 1 Columbia University 2 Stony Brook University |
| Pseudocode | No | The paper contains mathematical proofs and claims but does not include structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper is theoretical and does not mention releasing source code or provide any links to a code repository. |
| Open Datasets | No | The paper is theoretical and does not use or refer to any datasets for training. |
| Dataset Splits | No | The paper is theoretical and does not describe any validation dataset splits or processes. |
| Hardware Specification | No | The paper is theoretical and does not mention any specific hardware used for experiments. |
| Software Dependencies | No | The paper is theoretical and does not mention any specific software dependencies with version numbers for replication. |
| Experiment Setup | No | The paper is theoretical and does not describe any experimental setup details such as hyperparameters or training configurations. |