Principal components analysis (PCA) is one of the most widely used techniques in machine learning and data mining. Minor components analysis (MCA) is less well known, but can also...
Max Welling, Felix V. Agakov, Christopher K. I. Wi...
We describe a neurally-inspired, unsupervised learning algorithm that builds a non-linear generative model for pairs of face images from the same individual. Individuals are then ...
One of the principal advantages of parallelizing a rule-based system, or more generally, any A.I. system, is the ability to pursue alternate search paths concurrently. Conventiona...
We present an interactive technique for the registration of captured images of elastic and rigid body parts in which the user is given flexible control over material specific de...
Controller synthesis consists in automatically building controllers taking as inputs observation data and returning outputs guaranteeing that the controlled system satisfies some d...