Abstract. This paper describes a method of adapting a domain-independent HPSG parser to a biomedical domain. Without modifying the grammar and the probabilistic model of the origin...
In a previous paper we proposed Web-based language models relying on the possibility theory. These models explicitly represent the possibility of word sequences. In this paper we ...
Stanislas Oger, Vladimir Popescu, Georges Linar&eg...
We propose a general method for reranker construction which targets choosing the candidate with the least expected loss, rather than the most probable candidate. Different approac...
We present sparse topical coding (STC), a non-probabilistic formulation of topic models for discovering latent representations of large collections of data. Unlike probabilistic t...
Previous stochastic approaches to generation do not include a tree-based representation of syntax. While this may be adequate or even advantageous for some applications, other app...