… Thus robust independent subspace analysis network, optimized by sparse and soft … , is
first proposed to extract the latent spatial information of multi-view data with subspace bases. …

… constraint where the sample correlation between every pair of separated signals equals zero.
This constraint … ) imply that vectors V1w1 and Vzw1 are orthogonal to the subspace Im Wz …

… The theoretical part of this paper will be constrained to the determined case, which … subspaces
of components that are mutually independent while components inside of the subspaces …

… The signal subspace from all subjects is concatenated to form a tall data … to extract a
common signal subspace. ICA is applied on the group-level PCs in order to estimate independent …

… the assumption of a common subspace among all subjects and hence… independent
component is extracted as the closest one to the reference signal. Thus, the thresholding-constrained …

… In this work, we propose a new method, which we call, independent vector analysis (IVA)
for common subspace extraction (IVA-CS) to extract subspaces from large-scale datasets and …

… The subspace constraints to be exploited in this paper are derived from the relative affine
transformations collected from homogeneous color regions. Our algorithm assumes that each …

In this paper we propose a dimension reduction method for estimating the directions in a
multiple-index regression based on information extraction. This extends the recent work of Yin …

… constraints between the signal and background subspaces are imposed to regularize the
separation. The problem can then be posed as a constrained … as independent vector extraction …

… Abstract—We propose a novel technique for the extraction of one independent component
… subspaces are constrained to be orthogonal to ensure their uncorrelatedness. The constraint …