Learning Bayesian Belief Networks (BBN) from corpora and incorporating the extracted inferring knowledge with a Support Vector Machines (SVM) classifier has been applied to charac...
Abstract. Markov Random Fields (MRFs) are a popular and wellmotivated model for many medical image processing tasks such as segmentation. Discriminative Random Fields (DRFs), a dis...
Chi-Hoon Lee, Mark Schmidt, Albert Murtha, Aalo Bi...
Based on Information Theory, optimal feature selection should be carried out by searching Markov blankets. In this paper, we formally analyze the current Markov blanket discovery ...
Conventional speculative architectures use branch prediction to evaluate the most likely execution path during program execution. However, certain branches are difficult to predic...
Artur Klauser, Todd M. Austin, Dirk Grunwald, Brad...
The Single Instruction Multiple Data (SIMD) model for fine-grained parallelism was recently extended to support SIMD operations on disjoint vector elements. In this paper we demon...