A common approach in machine learning is to use a large amount of labeled data to train a model. Usually this model can then only be used to classify data in the same feature spac...
The paper provides an insight into the changing nature of the learning process through the adoption of interactive new media solutions into a traditional University Campus. The us...
In this paper we model relational random variables on the edges of a network using Gaussian processes (GPs). We describe appropriate GP priors, i.e., covariance functions, for dir...
This work represents the first step towards a task library system in the reinforcement learning domain. Task libraries could be useful in speeding up the learning of new tasks th...
James L. Carroll, Todd S. Peterson, Kevin D. Seppi
Abstract. In this paper we present three methods for image autoannotation used by the Wroclaw University of Technology group at ImageCLEF 2010 Photo Annotation track. All of our ex...