Subspace clustering refers to the problem of clustering data drawn from a union of low-dimensional subspaces of a high-dimensional space. State-of-the-art subspace clustering methods are based on expressing each data point as a linear combination of other data points while regularizing the matrix of coefficients with the L1, L2, or nuclear norms...
Creator:
Vidal, René (Johns Hopkins University)
Created:
2016-09-16
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.