Secretary Matching with Vertex Arrivals and No Rejections
Authors: Mohak Goyal5051-5058
AAAI 2022 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | All our algorithms run in polynomial time. The competitive analysis results hold in expectation, which is taken over the randomness in the arrival order and in the algorithm. |
| Researcher Affiliation | Academia | Department of Management Science & Engineering, Stanford University mohakg@stanford.edu |
| Pseudocode | Yes | Algorithm 1: ALG1 for BIPARTITEMATCHING1; Algorithm 2: ALG2 for BIPARTITEMATCHING2; Algorithm 3: ALG3 for GENERALMATCHING; Algorithm 4: ALG4 for ROOMMATEMATCHING |
| Open Source Code | No | The paper mentions an 'arxiv preprint arxiv:2112.07140' but does not state that source code for the described methods is openly available. |
| Open Datasets | No | The paper operates on theoretical graph models with arbitrary non-negative edge-weights and does not describe experiments using specific datasets for training. |
| Dataset Splits | No | The paper is theoretical and does not involve empirical validation on datasets, thus no dataset splits for validation are mentioned. |
| Hardware Specification | No | The paper focuses on theoretical algorithms and their competitive analysis, not empirical experiments. Therefore, no hardware specifications are mentioned. |
| Software Dependencies | No | The paper is theoretical and does not describe an implementation, hence no specific software dependencies with version numbers are provided. |
| Experiment Setup | No | The paper describes algorithmic phases and parameters (e.g., stopping points k, ke, ks) inherent to the algorithms themselves, but these are not experimental setup details like hyperparameters for a machine learning model training. |