Graph transduction methods label input data by learning a classification function that is regularized to exhibit smoothness along a graph over labeled and unlabeled samples. In pr...
We present a reinforcement learning architecture, Dyna-2, that encompasses both samplebased learning and sample-based search, and that generalises across states during both learni...
The Viterbi algorithm is an efficient and optimal method for decoding linear-chain Markov Models. However, the entire input sequence must be observed before the labels for any tim...
We explore the situation in which documents have to be categorized into more than one category system, a situation we refer to as multiple-view categorization. More particularly, ...
We consider boosting algorithms that maintain a distribution over a set of examples. At each iteration a weak hypothesis is received and the distribution is updated. We motivate t...