Author

Cristian Boldrin

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Preprint Sep 2026

Single-Pass Estimation of the Clustering Coefficient Distribution in Graph Streams

Triangle counting is one of the most fundamental problems in network analysis. Given the massive sizes of real-world graphs, there is a long history of small-space streaming algorithms providing accurate estimates for this problem. However, most of the results focus on estimating the total triangle count or the number...

Cristian Boldrin, C. Seshadhri · 0 citations

Jul 2026

Sensitivity Sampling with Predictions for k-Means Clustering

This work formally proves that current theoretical results on coresets construction via sensitivity sampling hold for coarser approximations of sensitivities compared to the one required by existing approaches, and proposes a natural predictor, which applies to the common scenario where clustering is performed on a seq...

Cristian Boldrin, Fabio Vandin · arXiv.org · 0 citations