Recently, supervised dimensionality reduction has been gaining attention, owing to the realization that data labels are often available and indicate important underlying structure...
In this paper, we present a mixture Principal Component Analysis (mPCA)-based approach for voxel level quantification of dynamic positron emission tomography (PET) data in brain s...
Probabilistic relational PCA (PRPCA) can learn a projection matrix to perform dimensionality reduction for relational data. However, the results learned by PRPCA lack interpretabi...
To support real-time tracking of objects in video sequences, there has been considerable effort directed at developing optical flow and general motion-based image segmentation alg...
Michael E. Farmer, Xiaoguang Lu, Hong Chen, Anil K...
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...