Miguel Ballesteros

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Chris DyerDeepMind, Carnegie MellonVerified email at google.com
Guillaume LampleResearch Scientist, Facebook AI ResearchVerified email at fb.com
Noah A. SmithUniversity of Washington; Allen Institute for Artificial IntelligenceVerified email at cs.washington.edu
Sandeep SubramanianMila, University of MontrealVerified email at umontreal.ca
Graham NeubigAssociate Professor of Computer Science, Carnegie Mellon UniversityVerified email at cs.cmu.edu
Adhiguna KuncoroOxford University and Google DeepMindVerified email at google.com
Kawakami KazuyaUniversity of Oxford, Department of Computer ScienceVerified email at cs.ox.ac.uk
Joakim NivreProfessor of Computational Linguistics, Uppsala UniversityVerified email at lingfil.uu.se
Austin MatthewsCarnegie Mellon UniversityVerified email at cmu.edu
Yoav GoldbergProfessor, Bar Ilan UniversityVerified email at cs.biu.ac.il
Leo WannerICREA Research Professor, Pompeu Fabra UniversityVerified email at upf.edu
Pablo GervásCatedrático de UniversidadVerified email at ucm.es
Waleed AmmarGoogleVerified email at allenai.org
Virginia FranciscoAssistant Professor of Computer Science, University Complutense of MadridVerified email at fdi.ucm.es
Bernd BohnetResearch Scientist, GoogleVerified email at google.com
Simon MilleUniversitat Pompeu FabraVerified email at upf.edu
Francesco BarbieriSnap Inc.Verified email at snap.com
Lingpeng KongGoogle DeepMind, The University of Hong KongVerified email at cs.hku.hk
Horacio SaggionProfesor Agregado, Department of Information & Communication Technologies, Universitat Pompeu FabraVerified email at upf.edu
Alberto DíazProfesor Titular de UniversidadVerified email at fdi.ucm.es

Miguel Ballesteros

Senior Applied Scientist, Amazon

Verified email at amazon.com - Homepage

Natural Language Processing Deep Learning Computational Linguistics all_pubs_hand_verified_to_be_actually_mine


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Neural Architectures for Named Entity Recognition G Lample, M Ballesteros, S Subramanian, K Kawakami, C Dyer Proceedings of NAACL 2016, 2016	2843	2016
Transition-Based Dependency Parsing with Stack Long Short-Term Memory C Dyer, M Ballesteros, W Ling, A Matthews, NA Smith Proceedings of ACL 2015, 2015	823	2015
Recurrent Neural Network Grammars C Dyer, A Kuncoro, M Ballesteros, NA Smith Proceedings of NAACL 2016, 2016	455	2016
Dynet: The dynamic neural network toolkit G Neubig, C Dyer, Y Goldberg, A Matthews, W Ammar, A Anastasopoulos, ... arXiv preprint arXiv:1701.03980, 2017	364*	2017
Improved Transition-Based Parsing by Modeling Characters instead of Words with LSTMs M Ballesteros, C Dyer, NA Smith Proceedings of EMNLP 2015, 2015	295	2015
Many languages, one parser W Ammar, G Mulcaire, M Ballesteros, C Dyer, NA Smith Transactions of the Association for Computational Linguistics (TACL), 2016	192	2016
Universal Dependencies 1.2 J Nivre, Ž Agić, MJ Aranzabe, M Asahara, A Atutxa, M Ballesteros, J Bauer, ... Universal Dependencies Consortium, 2015	162*	2015
What Do Recurrent Neural Network Grammars Learn About Syntax? A Kuncoro, M Ballesteros, L Kong, C Dyer, G Neubig, NA Smith Proceedings EACL 2017, 2017	114	2017
Are Emojis Predictable? F Barbieri, M Ballesteros, H Saggion Proceedings of Short Papers EACL 2017, 2017	96	2017
Universal Dependencies 2.1 J Nivre, Ž Agić, L Ahrenberg, L Antonsen, MJ Aranzabe, M Asahara, ... LINDAT/CLARIN digital library at the Institute of Formal and Applied …, 2017	82*	2017
MaltOptimizer: an optimization tool for MaltParser M Ballesteros, J Nivre Proceedings of the Demonstrations at EACL 2012, 2012	80	2012
Detecting readers with dyslexia using machine learning with eye tracking measures L Rello, M Ballesteros proceedings of the 12th Web for All Conference, 1-8, 2015	76	2015
Distilling an Ensemble of Greedy Dependency Parsers into One MST Parser A Kuncoro, M Ballesteros, L Kong, C Dyer, NA Smith Proceedings of EMNLP 2016, 2016	71	2016
Training with Exploration Improves a Greedy Stack-LSTM Parser M Ballesteros, Y Goldberg, C Dyer, NA Smith Proceedings of Short Papers EMNLP 2016, 2016	70	2016
MaltOptimizer: A System for MaltParser Optimization. M Ballesteros, J Nivre Proceedings of LREC 2012, 2012	69	2012
Semeval 2018 task 2: Multilingual emoji prediction F Barbieri, J Camacho-Collados, F Ronzano, LE Anke, M Ballesteros, ... Proceedings of The 12th International Workshop on Semantic Evaluation, 24-33, 2018	66	2018
Universal dependencies 2.0 (2017) J Nivre, Ž Agić, L Ahrenberg, MJ Aranzabe, M Asahara, A Atutxa, ... URL http://hdl. handle. net/11234/1-1983. LINDAT/CLARIN digital library at …, 2017	59*	2017
Scheduled Multi-Task Learning: From Syntax to Translation E Kiperwasser, M Ballesteros Transactions of the Association for Computational Linguistics, 2018 …, 2018	57	2018
Neural Language Models as Psycholinguistic Subjects: Representations of Syntactic State R Futrell, E Wilcox, T Morita, P Qian, M Ballesteros, R Levy Proceedings of NAACL 2019, 2019	56	2019
Greedy, Joint Syntactic-Semantic Parsing with Stack LSTMs S Swayamdipta, M Ballesteros, C Dyer, NA Smith Proceedings of CoNLL 2016, 2016	49	2016

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