We discuss a Probably Approximate Correct (PAC) learning paradigm for Boolean formulas, which we call PAC meditation, where the class of formulas to be learnt is not known in advan...
Bruno Apolloni, Andrea Brega, Dario Malchiodi, Gio...
We present a statistical generative model for unsupervised learning of verb argument structures. The model was used to automatically induce the argument structures for the 1,500 mo...
Thiago Alexandre Salgueiro Pardo, Daniel Marcu, Ma...
Distributional similarity has been widely used to capture the semantic relatedness of words in many NLP tasks. However, various parameters such as similarity measures must be hand...
We present an approach that combines bag-of-words and spatial models to perform semantic and syntactic analysis for recognition of an object based on its internal appearance and i...
The emergence of collaborative tagging systems with their underlying flat and uncontrolled resource organization paradigm has led to a large number of research activities focussi...