Federated Hierarchical Clustering with Automatic Selection of Optimal Cluster Numbers

ArXi:2603.12684v1 Announce Type: cross Federated Clustering (FC) is an emerging and promising solution in exploring data distribution patterns from distributed and privacy-protected data in an unsupervised manner. Existing FC methods implicitly rely on the assumption that clients are with a known number of uniformly sized clusters. However, the true number of clusters is typically unknown, and cluster sizes are naturally imbalanced in real scenarios.