We use a generative history-based model to predict the most likely derivation of a dependency parse. Our probabilistic model is based on Incremental Sigmoid Belief Networks, a rec...
Abstract. Accurate and fine-grained prediction of future user location and geographical profile has interesting and promising applications including targeted content service, adv...
We introduce a new task-independent framework to model top-down overt visual attention based on graphical models for probabilistic inference and reasoning. We describe a Dynamic B...
Software engineering has traditionally focussed on functional requirements and how to build software that has few bugs and can be easily maintained. Most design approaches include...
A distributed robot control system is proposed based on a temporal self-organizing neural network, called competitive and temporal Hebbian (CTH) network. The CTH network can learn ...