This paper describes a fully automatic twostage machine learning architecture that learns temporal relations between pairs of events. The first stage learns the temporal attribut...
Abstract. Algorithmic skeletons are a well-known approach for implementing parallel and distributed applications. Declarative versions typically use higher-order functions in funct...
We present an extensible supervised Target-Word Sense Disambiguation system that leverages upon GATE (General Architecture for Text Engineering), NSP (Ngram Statistics Package) an...
Mahesh Joshi, Serguei V. S. Pakhomov, Ted Pedersen...
Learning to recognize or predict sequences using long-term context has many applications. However, practical and theoretical problems are found in training recurrent neural networ...
The spatial distribution and time course of electrical signals in neurons have important theoretical and practical consequences. Because it is difficult to infer how neuronal form...
Nicholas T. Carnevale, Kenneth Y. Tsai, Brenda J. ...