The min-sum k-clustering problem is to partition a metric space (P, d) into k clusters C1, . . . , Ck ⊆ P such that k i=1 p,q∈Ci d(p, q) is minimized. We show the first effi...
Information diffusion, viral marketing, and collective classification all attempt to model and exploit the relationships in a network to make inferences about the labels of nodes....
Tracking heart motion plays an essential role in the diagnosis of cardiovascular diseases. This study investigates overlap priors for variational tracking of the Left Ventricle (LV...
Background: Recently, mass spectrometry data have been mined using a genetic algorithm to produce discriminatory models that distinguish healthy individuals from those with cancer...
Classification is an important problem in data mining. Given a database of records, each with a class label, a classifier generates a concise and meaningful description for each c...