Nearly every structured prediction problem in computer vision requires approximate inference due to large and complex dependencies among output labels. While graphical models prov...
Ubiquitous computing has established a vision of computation where computers are so deeply integrated into our lives that they become both invisible and everywhere. In order to ha...
An important task in machine learning is determining which learning algorithm works best for a given data set. When the amount of data is small the same data needs to be used repea...
Learning the parameters (conditional and marginal probabilities) from a data set is a common method of building a belief network. Consider the situation where we have known graph s...
Background: With the rapid expansion of DNA sequencing databases, it is now feasible to identify relevant information from prior sequencing projects and completed genomes and appl...