Markus Dreyer

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Jason EisnerProfessor of Computer Science, Johns Hopkins UniversityVerified email at cs.jhu.edu
Ariya RastrowAmazon.comVerified email at amazon.com
Ankur GandheScientist, AmazonVerified email at amazon.com
Anjishnu KumarMachine Learning Scientist, Amazon AlexaVerified email at amazon.com
Björn HoffmeisterAmazonVerified email at amazon.com
Lambert MathiasResearch Scientist, FacebookVerified email at fb.com
Sanjeev KhudanpurThe Johns Hopkins UniversityVerified email at jhu.edu
Mark DredzeJohns Hopkins UniversityVerified email at cs.jhu.edu
Keith HallGoogle ResearchVerified email at google.com
Noah A. SmithUniversity of Washington; Allen Institute for Artificial IntelligenceVerified email at cs.washington.edu
David A. SmithAssociate Professor, College of Computer and Information Science, Northeastern UniversityVerified email at ccs.neu.edu
Damianos KarakosRaytheon BBN TechnologiesVerified email at raytheon.com
Stan PeshterlievFacebookVerified email at fb.com
Emilio MontiSenior Applied Scientist at Amazon Alexa AIVerified email at amazon.co.uk
xing fanAmazonVerified email at amazon.com
Declan GrovesSenior Program Manager, MicrosoftVerified email at microsoft.com
Benjamin WellingtonResearch Analyst, Two Sigma InvestmentsVerified email at cs.nyu.edu
Tim FininWillard and Lillian Hackerman Chair in Engineering, University of Maryland, Baltimore CountyVerified email at umbc.edu
Paul McNameeJohns Hopkins UniversityVerified email at jhu.edu
David YarowskyProfessor of Computer Science, Johns Hopkins UniversityVerified email at jhu.edu

Markus Dreyer

Ph.D., Johns Hopkins University

Verified email at cs.jhu.edu

Natural Language Processing Machine Learning Machine Translation Morphology


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Latent-variable modeling of string transductions with finite-state methods M Dreyer, J Smith, J Eisner Proceedings of the 2008 Conference on Empirical Methods in Natural Language …, 2008	114	2008
Discovering morphological paradigms from plain text using a Dirichlet process mixture model M Dreyer, J Eisner Proceedings of the 2011 Conference on Empirical Methods in Natural Language …, 2011	97	2011
HyTER: Meaning-equivalent semantics for translation evaluation M Dreyer, D Marcu Proceedings of the 2012 Conference of the North American Chapter of the …, 2012	92	2012
Machine translation system combination using ITG-based alignments D Karakos, J Eisner, S Khudanpur, M Dreyer Proceedings of ACL-08: HLT, Short Papers, 81-84, 2008	70	2008
Just ASK: building an architecture for extensible self-service spoken language understanding A Kumar, A Gupta, J Chan, S Tucker, B Hoffmeister, M Dreyer, ... arXiv preprint arXiv:1711.00549, 2017	65	2017
LatticeRnn: Recurrent Neural Networks Over Lattices. F Ladhak, A Gandhe, M Dreyer, L Mathias, A Rastrow, B Hoffmeister Interspeech, 695-699, 2016	56	2016
Transfer learning for neural semantic parsing X Fan, E Monti, L Mathias, M Dreyer arXiv preprint arXiv:1706.04326, 2017	54	2017
Method and system for automatic management of reputation of translators D Marcu, M Dreyer US Patent 10,261,994, 2019	50	2019
HLTCOE approaches to knowledge base population at TAC 2009 P McNamee, M Dredze, A Gerber, N Garera, T Finin, J Mayfield, C Piatko, ... UMBC Faculty Collection, 2009	45	2009
Graphical models over multiple strings M Dreyer, J Eisner Proceedings of the 2009 Conference on Empirical Methods in Natural Language …, 2009	44	2009
Comparing reordering constraints for SMT using efficient BLEU oracle computation M Dreyer, K Hall, S Khudanpur Proceedings of the NAACL-HLT 2007/AMTA Workshop on Syntax and Structure in …, 2007	39	2007
Zero-Shot Learning Across Heterogeneous Overlapping Domains. A Kumar, PR Muddireddy, M Dreyer, B Hoffmeister INTERSPEECH, 2914-2918, 2017	34	2017
Vine parsing and minimum risk reranking for speed and precision M Dreyer, DA Smith, NA Smith Proceedings of the Tenth Conference on Computational Natural Language …, 2006	33	2006
A non-parametric model for the discovery of inflectional paradigms from plain text using graphical models over strings M Dreyer The Johns Hopkins University, 2011	25	2011
Better informed training of latent syntactic features M Dreyer, J Eisner Proceedings of the 2006 Conference on Empirical Methods in Natural Language …, 2006	25	2006
Lattice encoding using recurrent neural networks F Ladhak, A Gandhe, M Dreyer, A Rastrow, B Hoffmeister, L Mathias US Patent 10,176,802, 2019	24	2019
Final report of the 2005 language engineering workshop on statistical machine translation by parsing A Burbank, M Carpuat, S Clark, M Dreyer, P Fox, D Groves, K Hall, ... Johns Hopkins University, 2005	18	2005
Exploiting prosody for PCFGs with latent annotations. M Dreyer, I Shafran INTERSPEECH, 450-453, 2007	17	2007
Neural latent variable model for spoken language understanding A Kumar, M Dreyer US Patent 9,911,413, 2018	16	2018
Hill climbing on speech lattices: A new rescoring framework A Rastrow, M Dreyer, A Sethy, S Khudanpur, B Ramabhadran, M Dredze 2011 IEEE International Conference on Acoustics, Speech and Signal …, 2011	15	2011

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