Expected Probabilistic Hierarchies

Marcel Kollovieh, Bertrand Charpentier, Daniel Zügner, Stephan Günnemann

Neural Information Processing Systems 

Hierarchical clustering has usually been addressed by discrete optimization using heuristics or continuous optimization of relaxed scores for hierarchies. In this work, we propose to optimize expected scores under a probabilistic model over hierarchies.