Affinity Clustering: Hierarchical Clustering at Scale

Bateni, Mohammadhossein, Behnezhad, Soheil, Derakhshan, Mahsa, Hajiaghayi, MohammadTaghi, Kiveris, Raimondas, Lattanzi, Silvio, Mirrokni, Vahab

Neural Information Processing Systems 

Graph clustering is a fundamental task in many data-mining and machine-learning pipelines. In particular, identifying a good hierarchical structure is at the same time a fundamental and challenging problem for several applications. The amount of data to analyze is increasing at an astonishing rate each day. Hence there is a need for new solutions to efficiently compute effective hierarchical clusterings on such huge data. The main focus of this paper is on minimum spanning tree (MST) based clusterings.