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Matthew R. Gormley
Assistant Teaching Professor
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Research Interests:
Natural language processing: grammar induction, dependency parsing, semantic parsing, knowledge base population, coreference resolution, topic modeling, computational semantics.
Machine learning: approximate inference, unsupervised learning, decomposition techniques, nonparametrics, global optimization, low-resource learning, approximation-aware learning.
Natural language processing: grammar induction, dependency parsing, semantic parsing, knowledge base population, coreference resolution, topic modeling, computational semantics.
Machine learning: approximate inference, unsupervised learning, decomposition techniques, nonparametrics, global optimization, low-resource learning, approximation-aware learning.
Papers26 papers
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EMNLP, pp.4534-4542, (2020)
ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 32 (NIPS 2019), (2019)
Bibtex
NeurIPS, pp.13715-13725, (2019)
Cited by1EIBibtex
north american chapter of the association for computational linguistics, (2019)
Cited by1EIBibtex
(2018)
Cited by1Bibtex
ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 31 (NIPS 2018), (2018)
Cited by7EIBibtex
ACL, pp.2652-2662, (2018)
Cited by18EIBibtex
meeting of the association for computational linguistics, (2018)
THIRTY-FIRST AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, pp.4459-4465, (2017)
Cited by16EIBibtex
HLT-NAACL, (2016): 1019-1029
HLT-NAACL, pp.1374-1379, (2015)
Cited by40EIBibtex
Conference on Empirical Methods in Natural Language Processing, (2015): 1774-1784
ACL (Tutorial Abstracts), (2015)
Cited by4EIBibtex
Trans. Assoc. Comput. Linguistics, (2015): 489-501
Cited by16EIBibtex
HLT-NAACL, (2015)
Cited by4EIBibtex
ACL, pp.1177-1187, (2014)
Cited by24EIBibtex
ACL, pp.444-454, (2013)
Cited by13EIBibtex
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