We consider an interactive information retrieval task in which the user is interested in finding several to many relevant documents with minimal effort. Given an initial documen...
To date, many active learning techniques have been developed for acquiring labels when training data is limited. However, an important aspect of the problem has often been neglect...
This paper describes an application of active learning methods to the classification of phone strings recognized using unsupervised phonotactic models. The only training data req...
In the context of deployed spoken dialogue telecom services, we introduce a preprocessor called Fiction into the Spoken Language Understanding (SLU) component. It acts as an inter...
Meta-Learning has been used to select algorithms based on the features of the problems being tackled. Each training example in this context, i.e. each meta-example, stores the feat...