Ich stimme zu, dass diese Seite Cookies verwende. Weitere Informationen finden Sie unter unseren Datenschutzerklärungen .
X
Do Dinh, Erik-Lân
6  Ergebnisse:
OpenAccess-Volltexte X
Personensuche X
?
1

Predicting the Humorousness of Tweets Using Gaussian Proces..:

Miller, Tristan ; Do Dinh, Erik-Lân ; Simpson, Edwin.
https://doi.org/10.26342/2020-64-4.  , 2020
Link: http://hdl.handle.net/10..
 
?
2

Predicting Humorousness and Metaphor Novelty with Gaussian ..:

Simpson, Edwin ; Do Dinh, Erik-Lân ; Miller, Tristan.
Simpson , E , Do Dinh , E-L , Miller , T & Gurevych , I 2019 , Predicting Humorousness and Metaphor Novelty with Gaussian Process Preference Learning . in P Nakov & A Palmer (eds) , Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics . pp. 5716-5728 , 57th Annual Meeting of the Association for Computational Linguistics (ACL) , Florence , Italy , 28/07/19 . https://doi.org/10.18653/v1/P19-1572.  , 2019
Link: https://hdl.handle.net/1..
 
?
3

Metaphern digital – Auf dem Weg von der Annotation zur auto..:

Do Dinh, Erik-Lân ; Gerloff, Malte ; Núñez, Alexandra
doi:10.5281/zenodo.4645045.  , 2017
Link: https://zenodo.org/recor..
 
?
4

Predicting the Humorousness of Tweets Using Gaussian Proces..:

Miller, Tristan ; Dinh, Erik-Lân Do ; Simpson, Edwin.
http://arxiv.org/abs/2008.00853.  , 2020
Link: http://arxiv.org/abs/200..
 
?
5

EELECTION at SemEval-2017 Task 10: Ensemble of nEural Learn..:

Eger, Steffen ; Dinh, Erik-Lân Do ; Kuznetsov, Ilia..
http://arxiv.org/abs/1704.02215.  , 2017
Link: http://arxiv.org/abs/170..
 
?
6

Still not there? Comparing Traditional Sequence-to-Sequence..:

Schnober, Carsten ; Eger, Steffen ; Dinh, Erik-Lân Do.
http://arxiv.org/abs/1610.07796.  , 2016
Link: http://arxiv.org/abs/161..
 
1-6