Probabilistic model building methods can render difficult problems feasible by identifying and exploiting dependencies. They build a probabilistic model from the statistical prope...
We present a probabilistic, salience-based approach to the interpretation of pointing gestures together with spoken utterances. Our mechanism models dependencies between spatial a...
We present a probabilistic formulation of UCS (a sUpervised Classifier System). UCS is shown to be a special case of mixture of experts where the experts are learned independentl...
Narayanan Unny Edakunni, Tim Kovacs, Gavin Brown, ...
The application scenarios envisioned for ‘global ubiquitous computing’ have unique requirements that are often incompatible with traditional security paradigms. One alternativ...
We propose and analyze a distribution learning algorithm for a subclass of Acyclic Probabilistic Finite Automata (APFA). This subclass is characterized by a certain distinguishabi...