Required Reading

Related Papers:

[Book] Dependency Parsing, Sandra Kübler, Ryan McDonald, and Joakim Nivre, 2009, Chp 1,2,4
- Dependency Parsing, 1st-order Eisner Algorithm
- http://www.morganclaypool.com/doi/abs/10.2200/S00169ED1V01Y200901HLT002
Michael Collins. Discriminative Training Methods for Hidden Markov Models: Theory and Experiments with Perceptron Algorithms. EMNLP 2002. (Received Best Paper Award.)
- Perceptron Algorithm
- http://www.cs.columbia.edu/~mcollins/papers/tagperc.pdf
Ryan McDonald's thesis:
- Dependency Parsing, 1st-order & 2nd order Eisner Algorithm, 1st order & 2nd order feature set(English) p52
- http://www.ryanmcd.com/papers/thesis.pdf
Xavier Carreras, Michael Collins, and Terry Koo. TAG, Dynamic Programming and the Perceptron for Efficient, Feature-rich Parsing. In Proceedings of CONLL 2008. (Received Best Paper Award.)
- Tree Adjoin Grammar (TAG)
- http://www.cs.columbia.edu/~mcollins/papers/conll.final.pdf
Dong's thesis (Chapter 2)
- Perceptron, Average Perceptron
- http://www.cs.sfu.ca/~anoop/students/dsong/dsong_msc_thesis.pdf
Michael Collins. Ranking algorithms for named entity extraction: Boosting and the voted perceptron. ACL 2002.
- Average Perceptron
- http://aclweb.org/anthology/P/P02/P02-1062.pdf
Terry Koo, Michael Collins, Efficient Third-order Dependency Parsers
- 2nd-order & 3rd-order Eisner
- http://www.cs.columbia.edu/~mcollins/papers/koo10acl.pdf