2 papers
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.DS2024
Fast and Accurate Triangle Counting in Graph Streams Using Predictions
Cristian Boldrin, Fabio Vandin
In this work, we present the first efficient and practical algorithm for estimating the number of triangles in a graph stream using predictions. Our algorithm combines waiting room…