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Miguel Ballesteros
Miguel Ballesteros
Principal Applied Scientist, Amazon
Zweryfikowany adres z amazon.com - Strona główna
Tytuł
Cytowane przez
Cytowane przez
Rok
Neural Architectures for Named Entity Recognition
G Lample, M Ballesteros, S Subramanian, K Kawakami, C Dyer
Proceedings of NAACL 2016, 2016
48222016
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
10292015
Recurrent Neural Network Grammars
C Dyer, A Kuncoro, M Ballesteros, N Smith
Proceedings of NAACL 2016, 2016
690*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
444*2017
Improved Transition-Based Parsing by Modeling Characters instead of Words with LSTMs
M Ballesteros, C Dyer, NA Smith
Proceedings of EMNLP 2015, 2015
3392015
Many languages, one parser
W Ammar, G Mulcaire, M Ballesteros, C Dyer, NA Smith
Transactions of the Association for Computational Linguistics (TACL), 2016
2742016
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
1812015
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
1722019
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
1582017
Are Emojis Predictable?
F Barbieri, M Ballesteros, H Saggion
Proceedings of Short Papers EACL 2017, 2017
1512017
Universal dependencies 2.2
J Nivre, M Abrams, Z Agic, L Ahrenberg, L Antonsen, ...
Universal Dependencies Consortium, 2018
1422018
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
1312018
Universal dependencies 2.0
J Nivre, Ž Agić, L Ahrenberg, MJ Aranzabe, M Asahara, A Atutxa, ...
Universal Dependencies Consortium, 2017
117*2017
Universal dependencies 2.5
D Zeman, J Nivre, M Abrams, E Ackermann, N Aepli, H Aghaei, R Ziane
LINDAT/CLARIAHCZ digital library at the Institute of Formal and Applied …, 2020
1142020
MaltOptimizer: an optimization tool for MaltParser
M Ballesteros, J Nivre
Proceedings of the Demonstrations at EACL 2012, 2012
862012
Scheduled Multi-Task Learning: From Syntax to Translation
E Kiperwasser, M Ballesteros
Transactions of the Association for Computational Linguistics, 2018 …, 2018
852018
Universal Dependencies 2.1
J Nivre, Ž Agić, L Ahrenberg, L Antonsen, MJ Aranzabe, M Asahara, ...
Universal Dependencies Consortium, 2017
85*2017
Training with Exploration Improves a Greedy Stack-LSTM Parser
M Ballesteros, Y Goldberg, C Dyer, NA Smith
Proceedings of Short Papers EMNLP 2016, 2016
852016
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
832016
Multilingual Neural Machine Translation with Task-Specific Attention
G Blackwood, M Ballesteros, T Ward
Proceedings of COLING 2018, 2018
772018
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