Adapting Stable Matchings to Evolving Preferences

Authors: Robert Bredereck, Jiehua Chen, Dušan Knop, Junjie Luo, Rolf Niedermeier1830-1837

AAAI 2020 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Theoretical We obtain both hardness and tractability results, in particular showing a fixed-parameter tractability result with respect to the parameter distance between old and new stable matching. The paper focuses on complexity analysis, algorithm design, and mathematical proofs (e.g., Lemma 1, 2, 3, 4, theorems), which are characteristic of theoretical research.
Researcher Affiliation Academia 1Technische Universit at Berlin, Chair of Algorithmics and Computational Complexity 2Algorithms and Complexity Group, TU Wien, Vienna, Austria 3Department of Theoretical Computer Science, Faculty of Information Technology, Czech Technical University in Prague, Prague, Czech Republic
Pseudocode No The paper describes algorithmic steps and concepts (e.g., 'The algorithm behind Theorem 1 is partially inspired by...'), but does not include structured pseudocode blocks or figures labeled as 'Pseudocode' or 'Algorithm'.
Open Source Code No The paper does not provide any explicit statements about releasing source code or links to a code repository for the described methodology or experiments.
Open Datasets No The paper is theoretical and does not involve empirical studies or the use of datasets. Therefore, it does not describe or refer to any publicly available datasets for training.
Dataset Splits No The paper is theoretical and does not involve empirical studies with data. Therefore, it does not provide details on training, validation, or test dataset splits.
Hardware Specification No The paper is theoretical and does not involve empirical experiments requiring specific hardware. Therefore, no hardware specifications are provided.
Software Dependencies No The paper is theoretical and does not involve empirical experiments requiring specific software dependencies with version numbers. While it references theoretical algorithms, it does not list software used for implementation with version numbers.
Experiment Setup No The paper is theoretical and does not involve empirical experiments with a specific setup, such as hyperparameters or training configurations.