—This paper describes a new method to explore and discover within a large data set. We apply techniques from preference elicitation to automatically identify data elements that a...
In the Bayesian mixture modeling framework it is possible to infer the necessary number of components to model the data and therefore it is unnecessary to explicitly restrict the n...
This paper establishes a connection between two apparently very different kinds of probabilistic models. Latent Dirichlet Allocation (LDA) models are used as "topic models&qu...
Abstract— The need for efficient monitoring of spatiotemporal dynamics in large environmental surveillance applications motivates the use of robotic sensors to achieve sufficie...
Amarjeet Singh 0003, Fabio Ramos, Hugh D. Whyte, W...
Most previous work on trainable language generation has focused on two paradigms: (a) using a statistical model to rank a set of generated utterances, or (b) using statistics to i...