Bayesian learning in undirected graphical models--computing posterior distributions over parameters and predictive quantities-is exceptionally difficult. We conjecture that for ge...
Background: Novel strategies are required in order to handle the huge amount of data produced by microarray technologies. To infer gene regulatory networks, the first step is to f...
In this paper, we propose a framework that fuses multiple features for improved action recognition in videos. The fusion of multiple features is important for recognizing actions ...
In this paper we propose a Markov random field (MRF) based method for joint registration and segmentation of cardiac perfusion images, specifically the left ventricle (LV). MRFs ...
Kernel-based learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is perfor...
Gert R. G. Lanckriet, Nello Cristianini, Peter L. ...