Inverse Reinforcement Learning (IRL) is the problem of learning the reward function underlying a Markov Decision Process given the dynamics of the system and the behaviour of an e...
Dynamic Bayesian networks (DBNs) offer an elegant way to integrate various aspects of language in one model. Many existing algorithms developed for learning and inference in DBNs ...
Health care officials are increasingly concerned with knowing early whether an outbreak of a particular disease is unfolding. We often have daily counts of some variable that are ...
Background: In many approaches to the inference and modeling of regulatory interactions using microarray data, the expression of the gene coding for the transcription factor is co...
A key goal for the perceptual system is to optimally combine
information from all the senses that may be available in order to
develop the most accurate and unified picture possi...