Farhad Pourkamali-Anaraki, James Folberth, Stephen Becker
Sparse subspace clustering (SSC) clusters n points that lie near a union of low-dimensional subspaces. The SSC model expresses each point as a linear or affine combination of the other points, using either 1 or 0 regularization. Using 1 regularization results in a convex problem but requires O(n 2 ) storage, and is typically solved by the alternating direction method of multipliers which takes O(n 3 ) flops. The 0 model is non-convex but only needs memory linear in n, and is solved via orthogonal matching pur…
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