A wide range of computer programs, including compilers and theorem provers, manipulate data structures that involve names and binding. However, the design of programming idioms wh...
In this paper we propose a novel statistical language model to capture long-range semantic dependencies. Specifically, we apply the concept of semantic composition to the problem ...
Abstract. Domain-Specific Languages (DSL) offer many advantages over general languages, but their narrow scope makes them really effective only in very focused domains, for example...
The recent availability of large corpora for training N-gram language models has shown the utility of models of higher order than just trigrams. In this paper, we investigate meth...
We recapitulate regular one-shot learning from membership and equivalence queries, positive and negative finite data. We present a meta-algorithm that generalizes over as many sett...