We describe a hierarchical probabilistic model for the detection and recognition of objects in cluttered, natural scenes. The model is based on a set of parts which describe the e...
Erik B. Sudderth, Antonio B. Torralba, William T. ...
Geophysics research has been faced with a growing need for automated techniques with which to process large quantities of data. A successful tool must meet a number of requirements...
We consider the problem of inference from multinomial data with chances θ, subject to the a-priori information that the true parameter vector θ belongs to a known convex polytope...
This paper presents an analytical model to study how working sets scale with database size and other applications parameters in decision-support systems (DSS). The model uses appl...
We present an image synthesis methodology and a system built around it. Given a sparse set of photographs taken from unknown viewpoints, the system generates images from new, diff...