Spectral clustering, ordering and ranking extensively uses matrix-based methods and algorithms. This approach is amenable to vigorous analysis and is benefiting from a treasury of knowledge of linear algebra and applied mathematics accumulated through the centuries. This text presents recent advances in this subfield.
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