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cs.LG2026
Sensitivity Sampling with Predictions for k-Means Clustering
Cristian Boldrin, Fabio Vandin
We study the problem of k-means clustering on large datasets. The state-of-the-art for the problem is given by coresets-based approaches, which build small weighted summaries of th…
cs.DS2026
Scalable and Distributed Silhouette Approximation
Ilie Sarpe, Federico Altieri, Andrea Pietracaprina +2
The silhouette is one of the most widely used measures to assess the quality of a -clustering of a dataset of elements. Its evaluation requires no information beyond the clu…
cs.LG2026
Few-Shot Resampling for Scalable Statistically-Sound Data Mining
Leonardo Pellegrina, Fabio Vandin
A key step in knowledge discovery is the evaluation of data mining results. In several applications, including pattern mining, graph analysis, and others, this step includes the ev…