Background: Two central problems in computational biology are the determination of the alignment and phylogeny of a set of biological sequences. The traditional approach to this p...
With large amounts of correlated probabilistic data being generated in a wide range of application domains including sensor networks, information extraction, event detection etc.,...
Particle filters (PFs) are powerful samplingbased inference/learning algorithms for dynamic Bayesian networks (DBNs). They allow us to treat, in a principled way, any type of prob...
Arnaud Doucet, Nando de Freitas, Kevin P. Murphy, ...
Cognitive radio, which enables dynamic access of under-utilized licensed spectrums, is a promising technology for more efficient spectrum utilization. Since cognitive radio enables...
In this paper, we make a study on three Linear Discriminant Analysis (LDA) based methods: Regularized Discriminant Analysis (RDA), Discriminant Common Vectors (DCV) and Maximal Ma...