GOSUS: Grassmannian Online Subspace Updates with Structured-Sparsity
GOSUS: Grassmannian Online Subspace Updates with Structured-Sparsity
We study the problem of online subspace learning in the context of sequential observations involving structured perturbations. In online subspace learning, the observations are an unknown mixture of two components presented to the model sequentially - the main effect which pertains to the subspace and a residual/error term. If no …