Recently, relaxation approaches have been successfully used for MAP inference on NLP problems. In this work we show how to extend the relaxation approach to marginal inference use...
Discourse in formal domains, such as mathematics, is characterized by a mixture of telegraphic natural language and embedded formal expressions. Little is known about the suitabil...
We investigate a number of approaches to generating Stanford Dependencies, a widely used semantically-oriented dependency representation. We examine algorithms specifically design...
Daniel Cer, Marie-Catherine de Marneffe, Daniel Ju...
We present a method for detecting and parsing buildings from unorganized 3D point clouds into a compact, hierarchical representation that is useful for high-level tasks. The input...
We present new training methods that aim to mitigate local optima and slow convergence in unsupervised training by using additional imperfect objectives. In its simplest form, lat...
Valentin I. Spitkovsky, Hiyan Alshawi, Daniel Jura...