The Distortion of Threshold Approval Matching
Authors: Mohamad Latifian, Alexandros A. Voudouris
IJCAI 2024 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We show tight bounds on distortion of deterministic and randomized matching algorithms that are functions of the number of threshold utility levels. |
| Researcher Affiliation | Academia | 1University of Toronto, Canada 2University of Essex, UK latifian@cs.toronto.edu, alexandros.voudouris@essex.ac.uk |
| Pseudocode | No | The paper describes mechanisms using mathematical notation and prose (e.g., Definition 1, Definition 4), but it does not include structured pseudocode blocks or sections explicitly labeled "Algorithm" or "Pseudocode". |
| Open Source Code | No | No statement explicitly indicates that source code for the described methodology is available, nor is a specific repository link provided. |
| Open Datasets | No | This is a theoretical paper focused on deriving mathematical bounds and properties of mechanisms; it does not use or refer to any publicly available datasets for training or evaluation. |
| Dataset Splits | No | This is a theoretical paper and does not involve empirical validation on datasets, thus it does not provide details about training, validation, or test data splits. |
| Hardware Specification | No | This is a theoretical paper that focuses on mathematical analysis and algorithm design; it does not mention any specific hardware used for experiments. |
| Software Dependencies | No | This is a theoretical paper and does not describe any specific software dependencies or their version numbers required to replicate empirical experiments. |
| Experiment Setup | No | This is a theoretical paper and does not include details about an experimental setup, such as hyperparameters or system-level training settings. |