Výsledky vyhledávání - "Alaa Khaddaj"

Autor: Yiting Xia, Jonathan Leach, Ying Zhang, Alaa Khaddaj, Zhizhen Zhong, Manya Ghobadi

Publikováno v: SIGCOMM
SIGCOMM '21

Fiber cut events reduce the capacity of wide-area networks (WANs) by several Tbps. In this paper, we revive the lost capacity by reconfiguring the wavelengths from cut fibers into healthy fibers. We highlight two challenges that made prior solutions

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1d2a4ae23cb9e3d4a5fa4af613d8fc23
https://doi.org/10.1145/3452296.3472921

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Representation Learning for Improved Generalization of Adversarial Domain Adaptation with Text Classification

Autor: Alaa Khaddaj, Hazem Hajj

Publikováno v: ICIoT

Domain Adaptation techniques remain limited in accuracy and robustness due to data sparsity. In this paper, we present a new approach called Domain Adversarial network with Representation Learning (DARL), to improve domain adaptation by introducing a

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::b6748e357c1237f413e4ad99c7bc7145
https://doi.org/10.1109/iciot48696.2020.9089430

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Improved Generalization of Arabic Text Classifiers

Autor: Alaa Khaddaj, Wassim El-Hajj, Hazem Hajj

Publikováno v: WANLP@ACL 2019

While transfer learning for text has been very active in the English language, progress in Arabic has been slow, including the use of Domain Adaptation (DA). Domain Adaptation is used to generalize the performance of any classifier by trying to balan

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::b6f9a5e0d477857810d8dd0320ffa915
https://doi.org/10.18653/v1/w19-4618

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EMA at SemEval-2018 Task 1: Emotion Mining for Arabic

Autor: Obeida El Jundi, Alaa Khaddaj, Gilbert Badaro, Alaa Maarouf, Hazem Hajj, Raslan Kain, Wassim El-Hajj

Publikováno v: SemEval@NAACL-HLT

While significant progress has been achieved for Opinion Mining in Arabic (OMA), very limited efforts have been put towards the task of Emotion mining in Arabic. In fact, businesses are interested in learning a fine-grained representation of how user

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::1594b7f0de55eb58250ed5e300a535e3
https://doi.org/10.18653/v1/s18-1036

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