We focus on the problem of efficient learning of dependency trees. Once grown, they can be used as a special case of a Bayesian network, for PDF approximation, and for many other u...
The increasing use of temporal and spatial data in presentday relational systems necessitates an efficient support of joins on interval-valued attributes. Standard join algorithms...
—Identifying common patterns among area cladograms that arise in historical biogeography is an important tool for biogeographical inference. We develop the first rigorous formali...
Ganeshkumar Ganapathy, Barbara Goodson, Robert K. ...
A new method for tracking contours of moving objects in clutter is presented. For a given object, a model of its contours is learned from training data in the form of a subset of ...
The primary contribution of this paper is an algorithm capable of identifying parameters in certain mixed linear/nonlinear state-space models, containing conditionally linear Gauss...