Miguel Ballesteros

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Chris DyerDeepMind, Carnegie MellonVerified email at google.com
Sandeep SubramanianNVIDIAVerified email at umontreal.ca
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
Joakim NivreSenior Researcher, RISE; Professor of Computational Linguistics, Uppsala UniversityVerified email at ri.se
Adhiguna KuncoroOxford University and Google DeepMindVerified email at google.com
Kawakami KazuyaUniversity of Oxford, Department of Computer ScienceVerified email at cs.ox.ac.uk
Graham NeubigCarnegie Mellon University, Inspired CognitionVerified email at cs.cmu.edu
Austin MatthewsCarnegie Mellon UniversityVerified email at cmu.edu
Yoav GoldbergProfessor, Bar Ilan UniversityVerified email at cs.biu.ac.il
Pablo GervásCatedrático de UniversidadVerified email at ucm.es
Leo WannerICREA Research Professor, Pompeu Fabra UniversityVerified email at upf.edu
Waleed AmmarGoogleVerified email at google.com
Virginia FranciscoAssistant Professor of Computer Science, University Complutense of MadridVerified email at fdi.ucm.es
Francesco BarbieriSnap Inc.Verified email at snap.com
Simon MilleADAPT Research Centre, Dublin City UniversityVerified email at adaptcentre.ie
Bernd BohnetResearch Scientist, GoogleVerified email at google.com
Horacio SaggionChair in Computer Science & Artificial Intelligence, Department of Information & CommunicationVerified email at upf.edu
Lingpeng KongGoogle DeepMind, The University of Hong KongVerified email at cs.hku.hk
Luz RelloIE Business School, IE UniversityVerified email at ie.edu

Miguel Ballesteros

Principal 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	4210	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	968	2015
Recurrent Neural Network Grammars C Dyer, A Kuncoro, M Ballesteros, N Smith Proceedings of NAACL 2016, 2016	604*	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	422*	2017
Improved Transition-Based Parsing by Modeling Characters instead of Words with LSTMs M Ballesteros, C Dyer, NA Smith Proceedings of EMNLP 2015, 2015	330	2015
Many languages, one parser W Ammar, G Mulcaire, M Ballesteros, C Dyer, NA Smith Transactions of the Association for Computational Linguistics (TACL), 2016	249	2016
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	146	2017
Universal dependencies 2.2 J Nivre, M Abrams, Z Agic, L Ahrenberg, L Antonsen Universal Dependencies Consortium, 2018	136	2018
Detecting readers with dyslexia using machine learning with eye tracking measures L Rello, M Ballesteros Proceedings of the 12th International Web for All Conference, 1-8, 2015	134	2015
Are Emojis Predictable? F Barbieri, M Ballesteros, H Saggion Proceedings of Short Papers EACL 2017, 2017	132	2017
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	130	2019
Universal dependencies 2.0 J Nivre, Ž Agić, L Ahrenberg, MJ Aranzabe, M Asahara, A Atutxa, ... Universal Dependencies Consortium, 2017	113*	2017
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	112	2018
MaltOptimizer: an optimization tool for MaltParser M Ballesteros, J Nivre Proceedings of the Demonstrations at EACL 2012, 2012	84	2012
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	82	2016
Scheduled Multi-Task Learning: From Syntax to Translation E Kiperwasser, M Ballesteros Transactions of the Association for Computational Linguistics, 2018 …, 2018	80	2018
Training with Exploration Improves a Greedy Stack-LSTM Parser M Ballesteros, Y Goldberg, C Dyer, NA Smith Proceedings of Short Papers EMNLP 2016, 2016	80	2016
Universal Dependencies 2.1 J Nivre, Ž Agić, L Ahrenberg, L Antonsen, MJ Aranzabe, M Asahara, ... Universal Dependencies Consortium, 2017	78*	2017
MaltOptimizer: A System for MaltParser Optimization. M Ballesteros, J Nivre Proceedings of LREC 2012, 2012	71	2012
Multilingual Neural Machine Translation with Task-Specific Attention G Blackwood, M Ballesteros, T Ward Proceedings of COLING 2018, 2018	66	2018

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