An Analysis Framework for Metric Voting based on LP Duality
Authors: David Kempe2079-2086
AAAI 2020 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We provide a framework based on LP-duality and flow interpretations of the dual which provides a simpler and more unified way for proving upper bounds on the distortion of social choice rules. We prove that the distortion bound of 3 would follow from any of three combinatorial conjectures we formulate. We have verified the conjecture for n 7 using exhaustive computer search. |
| Researcher Affiliation | Academia | David Kempe University of Southern California |
| Pseudocode | No | The paper describes methods in prose and mathematical formulations but does not contain structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide an explicit statement about open-sourcing code or a link to a code repository for the methodology described. |
| Open Datasets | No | The paper is theoretical and does not refer to the use of any publicly available datasets for training or evaluation. |
| Dataset Splits | No | The paper is theoretical and does not discuss training, validation, or test dataset splits. |
| Hardware Specification | No | The paper does not provide any specific hardware details (e.g., GPU/CPU models, memory) used for running computations. |
| Software Dependencies | No | The paper does not list specific software dependencies with version numbers (e.g., library names, solvers, or frameworks). |
| Experiment Setup | No | The paper is theoretical and does not describe any experimental setup details, hyperparameters, or training configurations. |