We introduce and study Recursive Markov Chains (RMCs), which extend ordinary finite state Markov chains with the ability to invoke other Markov chains in a potentially recursive m...
Learning a tree substitution grammar is very challenging due to derivational ambiguity. Our recent approach used a Bayesian non-parametric model to induce good derivations from tr...
Children are facile at both discovering word boundaries and using those words to build higher-level structures in tandem. Current research treats lexical acquisition and grammar i...
We present a new approach to stochastic modeling of constraintbased grammars that is based on loglinear models and uses EM for estimation from unannotated data. The techniques are...
Stefan Riezler, Detlef Prescher, Jonas Kuhn, Mark ...
Domain specific programming languages tend to be rigid in capability and dependent on either a graphical interface or a scripting language. We present a question-oriented approach...