We describe a Bayesian inference algorithm that can be used to train any cascade of weighted finite-state transducers on end-toend data. We also investigate the problem of automat...
David Chiang, Jonathan Graehl, Kevin Knight, Adam ...
We show how features can easily be added to standard generative models for unsupervised learning, without requiring complex new training methods. In particular, each component mul...
Taylor Berg-Kirkpatrick, Alexandre Bouchard-C&ocir...
We present a tutorial on verification of safety properties for parameterized systems. Such a system consists of an arbitrary number of processes; the aim is to prove correctness of...
This paper proposes a novel semisupervised word alignment technique called EMDC that integrates discriminative and generative methods. A discriminative aligner is used to find hig...
Model minimization has been shown to work well for the task of unsupervised part-of-speech tagging with a dictionary. In (Ravi and Knight, 2009), the authors invoke an integer pro...
Sujith Ravi, Ashish Vaswani, Kevin Knight, David C...