Extreme k-Center Clustering
Authors: MohammadHossein Bateni, Hossein Esfandiari, Manuela Fischer, Vahab Mirrokni3941-3949
AAAI 2021 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Finally, we provide an empirical study to corroborate our theoretical guarantees, and demonstrate that the algorithm performs well in practice. |
| Researcher Affiliation | Collaboration | 1Google Research, NYC, New York, USA 2ETH, Zurich, Switzerland |
| Pseudocode | Yes | Algorithm 1 SAMPLE-AND-SOLVE(V , p, r) |
| Open Source Code | No | The paper does not provide any links or explicit statements about releasing source code for the methodology described. |
| Open Datasets | Yes | We employ 3 datasets in the experiments: two publicly available datasets (song (Dheeru and Karra Taniskidou 2017) and en-wiki (Epasto, Mirrokni, and Zadimoghaddam 2017)) and a much larger private one (prod). |
| Dataset Splits | No | The paper describes the datasets used for experiments but does not provide specific details on training, validation, or test dataset splits. |
| Hardware Specification | No | The paper states that experiments were run 'on a cloud platform (similar to Hadoop)' using 'no more than 100 machines', but it does not provide specific hardware details like CPU or GPU models for their algorithms. |
| Software Dependencies | No | The paper mentions that the algorithms were 'implemented... in C++', but does not provide specific version numbers for compilers, libraries, or other software dependencies. |
| Experiment Setup | No | The paper does not provide specific details on experimental setup, such as hyperparameter values or system-level training settings for their proposed algorithms. |