Experiments in High Energy Physics (HEP) generate tremendous amounts of data. For example, the accelerator at CERN is expected to generate petabytes per year. New HEP discoveries ...
Jagadeesh Kasaraneni, Theodore Johnson, Paul Avery
We develop a semi-supervised learning method that constrains the posterior distribution of latent variables under a generative model to satisfy a rich set of feature expectation c...
Abstract. Interest-based communities are a natural arrangement of distributed systems that prune the search space and allow for better dissemination of information to participating...
We present an example of a joint spatial and temporal task learning algorithm that results in a generative model that has applications for on-line visual control. We review work o...
We recall the basic idea of an algebraic approach to learning Bayesian network (BN) structures, namely to represent every BN structure by a certain (uniquely determined) vector, c...