ACL 2011 Tutorials

Here are some notes from the ACL tutorials:

Formal and Empirical Grammatical Inference
Jeffrey Heinz, Colin de la Higuera and Menno van Zaanen

Jeffrey and Colin motivated and presented the main results for formal grammatical inference. Even though many theoretical results are negative, learning is usually possible by restricting the model class (to a well defined subset used by natural languages) or assuming a non-distribution-free setting. Colin's book was recommended as a good introduction to the theory. It would be interesting to see if Turkish morphotactics or morphophonemics fall into one of the easy-to-learn model subclasses. You can download the slides.

Rich Prior Knowledge in Learning for Natural Language Processing
Gregory Druck, Kuzman Ganchev, Joao Graca

There is a recent trend for encoding prior knowledge in learning problems not in the prior distributions but later in the learning process. The prior knowledge usually comes in the form of feature-class expectations and guiding the model toward the correct expectations is only possible after considering the input. Posterior regularization, constraint driven learning, and generalized expectation criteria seem to be related implementations of this idea. You can download the slides.

Dual Decomposition for Natural Language Processing
Michael Collins and Alexander M Rush

I did not attend this one but here are the slides.