We report the results of fitting mixture models to the distribution of expression values for individual genes over a broad range of normal tissues, which we call the marginal expr...
Kernel Principal Component Analysis (KPCA) is a popular generalization of linear PCA that allows non-linear feature extraction. In KPCA, data in the input space is mapped to highe...
NiMo (Nets in Motion) is a visual environment aimed to support totally graphic programming in Data Flow style, with a strong functional inspiration. Solutions of growing complexit...
Gaussian processes have been widely used as a method for inferring the pose of articulated bodies directly from image data. While able to model complex non-linear functions, they ...
Label ranking is the task of inferring a total order over a predefined set of labels for each given instance. We present a general framework for batch learning of label ranking f...