Learning general functional dependencies is one of the main goals in machine learning. Recent progress in kernel-based methods has focused on designing flexible and powerful input...
Ioannis Tsochantaridis, Thomas Hofmann, Thorsten J...
This study examines the utility of meta-grammar constant generation on a series of benchmark problems. The performance of the meta-grammar approach is compared to a grammar which ...
We survey the use of weighted finite-state transducers (WFSTs) in speech recognition. We show that WFSTs provide a common and natural representation for HMM models, context-depend...
Unsupervised grammar induction is one of the most difficult works of language processing. Its goal is to extract a grammar representing the language structure using texts without a...
Abstract. Adaptive star grammars generalize well-known graph grammar formalisms based on hyperedge and node replacement while retaining, e.g., parseability and the commutativity an...