Citation Context

...the same subspace. SSC provides a powerful alternative to nearest neighbor (NN)-based approaches to subspace clustering and enables the derivation of guarantees that describe when convex methods [1], =-=[3]-=- or greedy algorithms [2] yield representations that only contain points from the same subspace. Formally, SSC computes sparse representations ci ∈ Rd for each point yi ∈ Rn, i = 1, . . . , d, via the...

Citation Context

...-dimensional data, such as images of faces acquired under varying illumination conditions, motion trajectories from different objects, or local field potentials in brainmachine-interface applications =-=[1]-=-, [2]. In order to use this signal model, the subspaces that the collection of data live upon must be learned from the data by performing subspace clustering—learning subspaces present in the data and...

Citation Context

...nsional data, such as images of faces acquired under varying illumination conditions, motion trajectories from different objects, or local field potentials in brainmachine-interface applications [1], =-=[2]-=-. In order to use this signal model, the subspaces that the collection of data live upon must be learned from the data by performing subspace clustering—learning subspaces present in the data and clus...