When students first learn programming, they often rely on a simple operational model of a program’s behavior to explain how particular features work. Because such models build o...
We propose a new language learning model that learns a syntactic-semantic grammar from a small number of natural language strings annotated with their semantics, along with basic ...
Semantic Role Labeling (SRL) has proved to be a valuable tool for performing automatic analysis of natural language texts. Currently however, most systems rely on a large training...
Abstract. The Bayesian approach to machine learning amounts to inferring posterior distributions of random variables from a probabilistic model of how the variables are related (th...
Automated deduction methods should be specified not procedurally, but declaratively, as inference systems which are proved correct regardless of implementation details. Then, di...