Abstract. State-of-the-art proof presentation systems suffer from several deficiencies. First, they simply present the proofs without motivating why the proof is done as it is do...
Abstract. Conventional artificial neural network models lack many physiological properties of the neuron. Current learning algorithms are more concerned to computational performanc...
We present an automated, scalable, method for crafting dynamic responses to real-time network requests. Specifically, we provide a flexible technique based on natural language pro...
Sam Small, Joshua Mason, Fabian Monrose, Niels Pro...
Human linguistic annotation is crucial for many natural language processing tasks but can be expensive and time-consuming. We explore the use of Amazon's Mechanical Turk syst...
Rion Snow, Brendan O'Connor, Daniel Jurafsky, Andr...
Unsupervised grammar induction is one of the most difficult works of language processing. Its goal is to extract a grammar representing the language structure using texts without a...