Abstract. Semantic inference is an important component in many natural language understanding applications. Classical approaches to semantic inference rely on logical representatio...
Ido Dagan, Roy Bar-Haim, Idan Szpektor, Iddo Green...
A class of discrete event synthesis problems can be reduced to solving language equations F • X ⊆ S, where F is the fixed component and S the specification. Sequential synthes...
Alan Mishchenko, Robert K. Brayton, Jie-Hong Rolan...
We present a neural-competitive learning model of language evolution in which several symbol sequences compete to signify a given propositional meaning. Both symbol sequences and p...
Statistical language models estimate the probability of a word occurring in a given context. The most common language models rely on a discrete enumeration of predictive contexts ...
John Blitzer, Kilian Q. Weinberger, Lawrence K. Sa...
We present a unified feature representation of 2.5D pointclouds and apply it to face recognition. The representation integrates local and global geometrical cues in a single compa...
Faisal R. Al-Osaimi, Mohammed Bennamoun, Ajmal S. ...