Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
Clustering Small Samples With Quality Guarantees: Adaptivity With One2all PPS
Authors: Edith Cohen, Shiri Chechik, Haim Kaplan
AAAI 2018 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We performed illustrative experiments for Euclidean k-means clustering on both synthetic and real-world data sets. We implemented our wrapper Algorithm 1 in numpy with the following base clustering algorithm A: We use 5 applications of KMEANS++ and take the set of k centroids that has the smallest clustering cost. This set is used as an initialization to 20 iterations of Lloyd s algorithm. The use of KMEANS++ to initialize Lloyd s algorithm is a prevalent method in practice. [...] Table 1 reports the results of our experiments. |
| Researcher Affiliation | Collaboration | Edith Cohen Google Research, USA Tel Aviv University, Israel Shiri Chechik Tel Aviv University, Israel Haim Kaplan Tel Aviv University, Israel |
| Pseudocode | Yes | Algorithm 1 Clustering Wrapper |
| Open Source Code | No | The paper does not provide an explicit statement or link to open-source code for the methodology described. |
| Open Datasets | Yes | MNIST and Fashion MNIST datasets: We use the MNIST data set of images of handwritten digits (Le Cun and Cortes 2010) and the Fashion data set of images of clothing items (Xiao, Rasul, and Vollgraf 2017). |
| Dataset Splits | No | The paper mentions using a "validation sample" in the Clustering Wrapper algorithm description, but it does not specify explicit training/validation/test dataset splits for the experiments conducted. |
| Hardware Specification | No | The paper does not provide specific details about the hardware used to run the experiments. |
| Software Dependencies | No | The paper mentions implementation in "numpy" but does not specify version numbers for numpy or any other software dependencies. |
| Experiment Setup | Yes | We use 5 applications of KMEANS++ and take the set of k centroids that has the smallest clustering cost. This set is used as an initialization to 20 iterations of Lloyd s algorithm. |