Professor, Computer Science,
University of Rochester.
Member, Center for Language Sciences
and Center for Computation and the Brain.
I'm interested in statistical approaches to natural
language processing, in particular for the tasks of
machine translation and
See my group and publications. Here are some recent papers:
- Synchronous Context-Free Grammars and Optimal Parsing Strategies,
Daniel Gildea and Giorgio Satta.
Computational Linguistics, to appear.
- Synchronous context-free grammars and optimal linear parsing strategies,
Pierluigi Crescenzi, Daniel Gildea, Andrea Marino, Gianluca Rossi, and Giorgio Satta.
Journal of Computer and System Sciences, 81(7):1333–1356, 2015.
- Automated prediction and analysis of job interview performance: The role of what you say and how you say it,
Iftekhar Naim, Mohammad Iftekhar Tanveer, Daniel Gildea, and Mohammed (Ehsan) Hoque.
In IEEE Conference on Automatic Face and Gesture Recognition, (FG), pp. 1–6, 2015.
- Discriminative Unsupervised Alignment of Natural Language Instructions with Corresponding Video Segments,
Iftekhar Naim, Young Chol Song, Qiguang Liu, Liang Huang, Henry Kautz, Jiebo Luo, and Daniel Gildea.
In Proceedings of the 2015 Meeting of the North American chapter of the Association for Computational Linguistics (NAACL-15),
- A Synchronous Hyperedge Replacement Grammar based approach for AMR parsing,
Xiaochang Peng, Linfeng Song, and Daniel Gildea.
In Proceedings of the Nineteenth Conference on Computational Natural Language Learning, 2015.
- Information Density and Syntactic Repetition,
David Temperley and Daniel Gildea.
Cognitive Science, pp. in press, 2015.
gildea @ cs rochester edu
July 11, 2016