ibe an abstract data model of protein structures by representing the geometry of proteins using spatial data types and present a framework for fast structural similarity search bas...
We use graphical models and structure learning to explore how people learn policies in sequential decision making tasks. Studies of sequential decision-making in humans frequently...
Abstract One approach to predict the secondary structure of RNA is the comparative approach. This approach is used when alignment of several homologous sequences of a RNA is availa...
Recently, the margin criterion has been successfully used for parameter optimization in graphical models. We introduce maximum margin based structure learning for Bayesian network...
XML and other semi-structured data may have partially specified or missing schema information, motivating the use of a structural summary which can be automatically computed from ...
Raghav Kaushik, Pradeep Shenoy, Philip Bohannon, E...