FSC selects m landmarks, builds an m-by-n sparse coefficient matrix, and derives the spectral embedding from its SVD, so both sparse coding and spectral clustering scale linearly with data size.
A geometric analysis of subspace clustering with outliers,
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Large-Scale Sparse Subspace Clustering Using Landmarks
FSC selects m landmarks, builds an m-by-n sparse coefficient matrix, and derives the spectral embedding from its SVD, so both sparse coding and spectral clustering scale linearly with data size.