In this paper we aim to train deep neural networks for rapid visual recognition. The task is highly challenging, largely due to the lack of a meaningful regularizer on the functio...
Prediction of gene functions is a major challenge to biologists in the post-genomic era. Interactions between genes and their products compose networks and can be used to infer ge...
In this paper, we present an approach for recovering a topological map of the environment using only detection events from a deployed sensor network. Unlike other solutions to this...
This paper focuses on technologies that enable meaningful, constructionist interaction in collaborative music environments. In particular, it describes the design and implementati...
Conor McCarthy, James Bligh, Kevin Jennings, Brend...
We propose a simple approach to combining first-order logic and probabilistic graphical models in a single representation. A Markov logic network (MLN) is a first-order knowledge b...