Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Ioannis Tsiamas"'
Speech translation models are unable to directly process long audios, like TED talks, which have to be split into shorter segments. Speech translation datasets provide manual segmentations of the audios, which are not available in real-world scenario
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9a4a38ac282a5eb246d1856806959300
https://hdl.handle.net/2117/387121
https://hdl.handle.net/2117/387121
Publikováno v:
Proceedings of the 19th International Conference on Spoken Language Translation (IWSLT 2022).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1008dbf9c50b9146dbe85bcb7a9cf1d5
https://doi.org/10.18653/v1/2022.iwslt-1.23
https://doi.org/10.18653/v1/2022.iwslt-1.23
Autor:
Marta R. Costa-jussà, Gerard I. Gállego, Ioannis Tsiamas, José A. R. Fonollosa, Carlos Escolano
Publikováno v:
UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
IWSLT
Universitat Politècnica de Catalunya (UPC)
IWSLT
This paper describes the submission to the IWSLT 2021 offline speech translation task by the UPC Machine Translation group. The task consists of building a system capable of translating English audio recordings extracted from TED talks into German te
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::437e2661bf92db25f318ed22cdaaa677
http://hdl.handle.net/2117/353117
http://hdl.handle.net/2117/353117
Autor:
Ioannis Tsiamas, Svetlana Borovkova
Publikováno v:
Borovkova, S & Tsiamas, I 2019, ' An ensemble of LSTM neural networks for high-frequency stock market classification ', Journal of Forecasting, vol. 38, no. 6, pp. 600-619 . https://doi.org/10.1002/for.2585
Journal of Forecasting, 38(6), 600-619. John Wiley and Sons Ltd
Journal of Forecasting, 38(6), 600-619. John Wiley and Sons Ltd
We propose an ensemble of long–short-term memory (LSTM) neural networks for intraday stock predictions, using a large variety of technical analysis indicators as network inputs. The proposed ensemble operates in an online way, weighting the individ
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7ebe71ba92f412b2ff50cc9e6a8d4d52
https://research.vu.nl/en/publications/f41b921e-1b60-4cce-9f47-020ca1e28f0d
https://research.vu.nl/en/publications/f41b921e-1b60-4cce-9f47-020ca1e28f0d
Publikováno v:
Annals of Data Science; Aug2024, Vol. 11 Issue 4, p1421-1434, 14p
Autor:
Borovkova, Svetlana1 (AUTHOR) s.a.borovkova@vu.nl, Tsiamas, Ioannis1 (AUTHOR)
Publikováno v:
Journal of Forecasting. Sep2019, Vol. 38 Issue 6, p600-619. 20p.
Autor:
Ferrando Monsonís, Javier, Gallego Olsina, Gerard Ion, Tsiamas, Ioannis, Ruiz Costa-jussà, Marta
Language Generation Models produce words based on the previous context. Although existing methods offer input attributions as explanations for a model's prediction, it is still unclear how prior words affect the model's decision throughout the layers
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______3484::d0a27181a8ba6104d91e39e4fa73adcd
https://hdl.handle.net/2117/390792
https://hdl.handle.net/2117/390792