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cs.LG2025
Hierarchical Linkage Clustering Beyond Binary Trees and Ultrametrics
Maximilien Dreveton, Matthias Grossglauser, Daichi Kuroda +1
Hierarchical clustering seeks to uncover nested structures in data by constructing a tree of clusters, where deeper levels reveal finer-grained relationships. Traditional methods,…
cs.LG2025
Optimal Graph Clustering without Edge Density Signals
Maximilien Dreveton, Elaine Siyu Liu, Matthias Grossglauser +1
This paper establishes the theoretical limits of graph clustering under the Popularity-Adjusted Block Model (PABM), addressing limitations of existing models. In contrast to the St…
cs.LG2025
Learn to Vaccinate: Combining Structure Learning and Effective Vaccination for Epidemic and Outbreak Control
Sepehr Elahi, Paula Mürmann, Patrick Thiran
The Susceptible-Infected-Susceptible (SIS) model is a widely used model for the spread of information and infectious diseases, particularly non-immunizing ones, on a graph. Given a…