We propose a simple approach to combining first-order logic and probabilistic graphical models in a single representation. A Markov logic network (MLN) is a first-order knowledge b...
For almost a century, the Harvard Business School has used case studies as the basis for experiential learning in both MBA and Executive Education courses. This article presents a...
Bayesian learning, widely used in many applied data-modeling problems, is often accomplished with approximation schemes because it requires intractable computation of the posterio...
The state-of-the-art object detection algorithm learns a binary classifier to differentiate the foreground object from the background. Since the detection algorithm exhaustively s...
This paper presents a spatial-semantic modeling system featuring automated learning of object-place relations from an online annotated database, and the application of these relat...
Pooja Viswanathan, David Meger, Tristram Southey, ...