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Trond Grenager
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2000 – 2009
- 2007
- [j1]Yoav Shoham, Rob Powers, Trond Grenager:
If multi-agent learning is the answer, what is the question? Artif. Intell. 171(7): 365-377 (2007) - [c11]Marie-Catherine de Marneffe, Trond Grenager, Bill MacCartney, Daniel M. Cer, Daniel Ramage, Chloé Kiddon, Christopher D. Manning:
Robust Graph Alignment Methods for Textual Inference and Machine Reading. AAAI Spring Symposium: Machine Reading 2007: 36-42 - [c10]Nathanael Chambers, Daniel M. Cer, Trond Grenager, David Hall, Chloé Kiddon, Bill MacCartney, Marie-Catherine de Marneffe, Daniel Ramage, Eric Yeh, Christopher D. Manning:
Learning Alignments and Leveraging Natural Logic. ACL-PASCAL@ACL 2007: 165-170 - [c9]Jenny Rose Finkel, Trond Grenager, Christopher D. Manning:
The Infinite Tree. ACL 2007 - 2006
- [c8]Trond Grenager, Christopher D. Manning:
Unsupervised Discovery of a Statistical Verb Lexicon. EMNLP 2006: 1-8 - [c7]Bill MacCartney, Trond Grenager, Marie-Catherine de Marneffe, Daniel M. Cer, Christopher D. Manning:
Learning to recognize features of valid textual entailments. HLT-NAACL 2006 - 2005
- [c6]Jenny Rose Finkel, Trond Grenager, Christopher D. Manning:
Incorporating Non-local Information into Information Extraction Systems by Gibbs Sampling. ACL 2005: 363-370 - [c5]Trond Grenager, Dan Klein, Christopher D. Manning:
Unsupervised Learning of Field Segmentation Models for Information Extraction. ACL 2005: 371-378 - 2004
- [c4]Yoav Shoham, Rob Powers, Trond Grenager:
On the Agenda(s) of Research on Multi-Agent Learning. AAAI Technical Report (2) 2004: 89-95 - [c3]Galen Andrew, Trond Grenager, Christopher D. Manning:
Verb Sense and Subcategorization: Using Joint Inference to Improve Performance on Complementary Task. EMNLP 2004: 150-157 - 2002
- [c2]Trond Grenager, Rob Powers, Yoav Shoham:
Dispersion Games: General Definitions and Some Specific Learning Results. AAAI/IAAI 2002: 398-403 - 2001
- [c1]Kazumi Saito, Pat Langley, Trond Grenager, Christopher Potter, Alicia Torregrosa, Steven A. Klooster:
Computational Revision of Quantitative Scientific Models. Discovery Science 2001: 336-349
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