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Large-Scale Spectral Clustering Based on Representative Points
2019
Mathematical Problems in Engineering
Spectral clustering (SC) has attracted more and more attention due to its effectiveness in machine learning. However, most traditional spectral clustering methods still face challenges in the successful application of large-scale spectral clustering problems mainly due to their high computational complexity οn3, where n is the number of samples. In order to achieve fast spectral clustering, we propose a novel approach, called representative point-based spectral clustering (RPSC), to efficiently
doi:10.1155/2019/5864020
fatcat:zvd737rgo5b3jidxpnoqbts3i4