In the context of classification problems, algorithms that generate multivariate trees are able to explore multiple representation languages by using decision tests based on a com...
Many new applications that involve decision making need online (i.e., OLAP-styled) preference analysis with multidimensional boolean selections. Typical preference queries includes...
We seek a framework that addresses localization, detection and recognition of man-made objects in natural-scene images in a unified manner. We propose to model artificial structur...
We present a novel framework for learning a joint shape and appearance model from a large set of un-labelled training examples in arbitrary positions and orientations. The shape an...
This paper presents a novel framework called proto-reinforcement learning (PRL), based on a mathematical model of a proto-value function: these are task-independent basis function...