A Brief Summary of Research Interests

Terry Koo
Michael Collins


I am a former graduate student of Michael Collins at MIT CSAIL. In previous work, I have received a B.S., M.Eng, and Ph.D in EECS at MIT. My research interests include structured classification, discriminative methods, and semi-supervised learning.

1  Introduction

I am an alumnus of MIT CSAIL, advised by Michael Collins. I am interested in discriminative modeling for structured classification and, more recently, in semi-supervised learning methods for NLP.

2  Dependency parsing

My research has focused on dependency parsing, a syntactic formalism whose grounded, lexicalized nature makes it an attractive target for feature-​rich discriminative models. At the same time, dependency parsers are able to recover core head-​modifier relationships.

3  Structured linear models

Structured linear models are a discriminative classification framework composed of three components: (1) a factorization, which specifies a decomposition of structured labels into sets of parts, allowing efficient decoding and inference; (2) a feature mapping, which represents each part as a vector of real-​valued features; and (3) a parameter estimation algorithm, which learns a weighting for each feature.
Each component can be improved in a modular fashion. For example, the factorization can be improved by using a second- or third-​order parser instead of a first-​order parser, features can be improved by adding cluster based information, and parameter estimation can be adjusted by selecting between the structured perceptron, max-​margin models, or log-​linear models.

4  Future work

I am currently at Google Research under the auspices of Fernando Pereira.


T. Koo and M. Collins. 2004. Parse Reranking with WordNet Using a Hidden-​Variable Model. M.Eng Thesis, Massachusetts Institute of Technology, Cambrige, MA, USA.
J. Hajič, M. Čmejrek, B. Dorr, Y. Ding, J. Eisner, D. Gildea, T. Koo, K. Parton, G. Penn, D. Radev, and O. Rambow. 2002. Natural Language Generation in the Context hyphenate of Machine Translation; Section 3.3, Chapter 6 (with Jan Hajič). NLP WS-02 Final Report.