In this paper, we propose a novel technique for the efficient prediction of multiple continuous target variables from high-dimensional and heterogeneous data sets using a hierarch...
Aleksandar Lazarevic, Ramdev Kanapady, Chandrika K...
Over the years, researchers in the image analysis community have successfully used various statistical modeling methods to segment, classify, and annotate digital images. In this ...
In this paper we propose a method for grouping and summarizing large sets of association rules according to the items contained in each rule. We use hierarchical clustering to par...
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...
Simultaneously segmenting and labeling images is a fundamental problem in Computer Vision. In this paper, we introduce a hierarchical CRF model to deal with the problem of labelin...