Recent work on unsupervised feature learning has shown that learning on polynomial expansions of input patches, such as on pair-wise products of pixel intensities, can improve the...
This chapter discusses decision making under uncertainty. More specifically, it offers an overview of efficient Bayesian and distribution-free algorithms for making near-optimal se...
We propose a new local learning scheme that is based on the principle of decisiveness: the learned classifier is expected to exhibit large variability in the direction of the test ...
Graph matching is a classical problem in pattern recognition with many applications, particularly when the graphs are embedded in Euclidean spaces, as is often the case for comput...
Julian McAuley, Teofilo de Campos, Tiberio Caetano
Learning Object repositories play a key role in the vision of reusable learning contents and learning designs, serving as providers for learning-oriented artefacts. Nevertheless, ...