Professor, Computer Science,
University of Rochester.
Member, Center for Language Sciences
and Institute for Data Science.
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:
- Addressing the Data Sparsity Issue in Neural AMR Parsing,
Xiaochang Peng, Chuan Wang, Daniel Gildea, and Nianwen Xue.
In Proceedings of the European Chapter of the ACL (EACL-17), 2017.
- Parsing Linear-Context Free Rewriting Systems with Fast Matrix Multiplication,
Shay B. Cohen and Daniel Gildea.
Computational Linguistics, 42(3):421–455, 2016.
- Synchronous Context-Free Grammars and Optimal Parsing Strategies,
Daniel Gildea and Giorgio Satta.
Computational Linguistics, 42(2):207–243, 2016.
- Aligning Movies with Scripts by Exploiting Temporal Ordering Constraints,
Iftekhar Naim, Abdullah Al Mamun, Young Chol Song, Jiebo Luo, Henry Kautz, and Daniel Gildea.
In 23rd International Conference on Pattern Recognition (ICPR), 2016.
- UofR at SemEval-2016 Task 8: Learning Synchronous Hyperedge Replacement Grammar for AMR Parsing,
Xiaochang Peng and Daniel Gildea.
In NAACL-HLT 2016 Workshop on Semantic Evaluation (SemEval-2016), 2016.
- AMR-to-text Generation as a Traveling Salesman Problem,
Linfeng Song, Yue Zhang, Xiaochang Peng, Zhiguo Wang, and Daniel Gildea.
In Conference on Empirical Methods in Natural Language Processing (EMNLP-16), 2016.
- Unsupervised Alignment of Actions in Video with Text Descriptions,
Young Chol Song, Iftekhar Naim, Abdullah Al Mamun, Kaustubh Kulkarni, Parag Singla, Jiebo Luo, Daniel Gildea, and Henry Kautz.
In Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI-16), 2016.
- Sense Embedding Learning for Word Sense Induction,
Linfeng Song, Zhiguo Wang, Haitao Mi, and Daniel Gildea.
In Fifth Joint Conference On Lexical And Computational Semantics (*SEM 2016), pp. 85–90, 2016.
- 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.
- Feature-based Decipherment for Large Vocabulary Machine Translation,
Iftekhar Naim and Daniel Gildea.
arXiv preprint 1508.02142, 2015.
gildea @ cs rochester edu
February 22, 2017