Discriminating Tensor Spectral Clustering for High-Dimension-Low-Sample-Size Data
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DOI: 10.1109/tnnls.2024.3422243
Abstract: Tensor spectral clustering (TSC) is a recently proposed approach to robustly group data into underlying clusters. Unlike the traditional spectral clustering (SC), which merely uses pairwise similarities of data in an affinity matrix, TSC aims… read more here.
Keywords: low sample; dimension; high dimension; dimension low ... See more keywords