Tournament Fixing Parameterized by Feedback Vertex Set Number Is FPT
Authors: Meirav Zehavi
AAAI 2023 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | A sequence of papers has studied the parameterized complexity of TOURNAMENT FIXING with respect to the feedback arc set number (fas) of D... We answer this question positively. In fact, although fvs can be arbitrarily smaller than fas, we attain the same dependency on the parameter in the time complexity. So, additionally, our work subsumes the best known algorithm for TOURNAMENT FIXING with respect to fas. |
| Researcher Affiliation | Academia | Meirav Zehavi* Department of Computer Science, Ben-Gurion University of the Negev, Beersheba, Israel meiravze@bgu.ac.il |
| Pseudocode | No | The paper describes the algorithm in a structured manner with definitions and recursive formulas, and outlines 'The Algorithm' in steps, but it does not include a formal 'Pseudocode' or 'Algorithm' block or figure. |
| Open Source Code | No | The paper does not provide any statement or link indicating that source code for the described methodology is publicly available. |
| Open Datasets | No | The paper is purely theoretical, focusing on algorithm design and complexity analysis. It does not involve empirical studies with datasets for training, validation, or testing. |
| Dataset Splits | No | The paper is purely theoretical, focusing on algorithm design and complexity analysis. It does not involve empirical studies and therefore does not specify training, validation, or test dataset splits. |
| Hardware Specification | No | The paper is theoretical and does not conduct experiments, therefore no hardware specifications are provided. |
| Software Dependencies | No | The paper is theoretical and does not conduct experiments, therefore no specific software dependencies with version numbers are listed. |
| Experiment Setup | No | The paper is theoretical and focuses on algorithm design and complexity. It does not describe an experimental setup with hyperparameters or system-level training settings. |