Title: Learning Graph Representations by Dendrograms,
Abstract: Hierarchical graph clustering is a common technique to reveal the multi-scale
structure of complex networks. We propose a novel metric for assessing the
quality of a hierarchical clustering. This metric reflects the ability to
reconstruct the graph from the dendrogram, which encodes the hierarchy. The
optimal representation of the graph defines a class of reducible linkages
leading to regular dendrograms by greedy agglomerative clustering.