We describe a set of supervised machine learning experiments centering on the construction of statistical models of WH-questions. These models, which are built from shallow lingui...
We present a knowledge and context-based system for parsing and translating natural language and evaluate it on sentences from the Wall Street Journal. Applying machine learning t...
We describe the use of a hierarchical topic model for automatically identifying syntactic and lexical patterns that explicitly state ontological relations. We leverage distant sup...
Graph matching is an important problem in computer
vision. It is used in 2D and 3D object matching and recognition.
Despite its importance, there is little literature on
learnin...
Abstract. We generalize a learning algorithm originally devised for deterministic all-accepting weighted tree automata (wta) to the setting of arbitrary deterministic wta. The lear...