Spectral Modification of Graphs for Improved Spectral Clustering

NeurIPS 2019 Ioannis KoutisHuong Le

Spectral clustering algorithms provide approximate solutions to hard optimization problems that formulate graph partitioning in terms of the graph conductance. It is well understood that the quality of these approximate solutions is negatively affected by a possibly significant gap between the conductance and the second eigenvalue of the graph... (read more)

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