We consider the problem of clustering data lying on multiple subspaces of unknown and possibly different dimensions. We show that one can represent the subspaces with a set of pol...
Subspace segmentation is the task of segmenting data
lying on multiple linear subspaces. Its applications in
computer vision include motion segmentation in video,
structure-from...
Random subspaces are a popular ensemble construction technique that improves the accuracy of weak classifiers. It has been shown, in different domains, that random subspaces combi...