Dynamic Facility Location in High Dimensional Euclidean Spaces
Authors: Sayan Bhattacharya, Gramoz Goranci, Shaofeng H.-C. Jiang, Yi Qian, Yubo Zhang
ICML 2024 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Experiments on real datasets confirm that our algorithm achieves high-quality solutions with low running time, and incurs minimal recourse. |
| Researcher Affiliation | Academia | 1University of Warwick, UK 2Faculty of Computer Science, University of Vienna, Austria 3Peking University, China. |
| Pseudocode | Yes | Algorithm 1 (Czumaj et al., 2024) on input point-set P... Algorithm 2 INSERT(p) |
| Open Source Code | No | The paper mentions 'Our implementation' but does not state it is open-source or provide a link to the code for the described methodology. |
| Open Datasets | Yes | Our experiment is done on Twitter (Chan et al., 2018b), Census1990 (Meek et al.), Covertype (Blackard, 1998) and KDD-Cup (Stolfo et al., 1999) datasets. |
| Dataset Splits | No | The paper specifies using a 'sliding window of size ℓ= 1000' but does not provide explicit training, validation, or test dataset splits (e.g., percentages or counts). |
| Hardware Specification | Yes | All the experiments are conducted on an Apple computer with M1 Pro CPU and 16GB memory. |
| Software Dependencies | No | The paper mentions implementation 'in C++ language' and use of 'standard locality-sensitive hashing (LSH) techniques' but does not specify version numbers for any software or libraries. |
| Experiment Setup | Yes | We consider a sliding window of size ℓ= 1000, and our update operations on the datasets are generated by this sliding window. The opening cost is set such that a moderate number of facilities would be open in a (near-)optimal solution. ... In our experiments, we use 15 random hash functions and we find this setup already produces decent accuracy when combining with our algorithm. |