Markov statistical methods may make it possible to develop an unsupervised learning process that can automatically identify genomic structure in prokaryotes in a comprehensive way...
"Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning...
Carl Edward Rasmussen and Christopher K. I. Willia...
We show that a wide class of bidirectional data-flow analyses and program optimizations based on them admit declarative descriptions in the form of type systems. The salient feat...
Modern software codebases are frequently large, heterogeneous, and constantly evolving. The languages and tools for software construction, including code builds and configuration m...
Supervised classification methods have been shown to be very effective for a large number of applications. They require a training data set whose instances are labeled to indicate...