This paper describes a new kind of language bias, S-structural indeterminate clauses, which takes into account the meaning of predicates that play a key role in the complexity of l...
Traditional Markov network structure learning algorithms perform a search for globally useful features. However, these algorithms are often slow and prone to finding local optima d...
Abstract--We study how to effectively integrate reinforcement learning (RL) and programming languages via adaptation-based programming, where programs can include non-deterministic...
We present a statistical generative model for unsupervised learning of verb argument structures. The model was used to automatically induce the argument structures for the 1,500 mo...
Thiago Alexandre Salgueiro Pardo, Daniel Marcu, Ma...
We present a large-margin formulation and algorithm for structured output prediction that allows the use of latent variables. Our proposal covers a large range of application prob...