I describe a framework for interpreting Support Vector Machines (SVMs) as maximum a posteriori (MAP) solutions to inference problems with Gaussian Process priors. This probabilisti...
Because of the great variability of factors to take into account, designing a spoken dialogue system is still a tailoring task. Rapid design and reusability of previous work is ma...
Based on Information Theory, optimal feature selection should be carried out by searching Markov blankets. In this paper, we formally analyze the current Markov blanket discovery ...
In this paper, we study cost-sensitive semi-supervised learning where many of the training examples are unlabeled and different misclassification errors are associated with unequa...
We present a perceptron-style discriminative approach to machine translation in which large feature sets can be exploited. Unlike discriminative reranking approaches, our system c...