Title: Learning Graph Representations by Dendrograms. Abstract: Hierarchical  clustering is a common approach to analysing  the 
multi-scale structure of  graphs observed in practice.  
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 encoding the hierarchy. The best  representation of the graph for this metric in turn yields a  novel hierarchical clustering algorithm. Experiments on both real and synthetic data illustrate the efficiency of the approach. 
