Zobrazeno 1 - 10
of 22
pro vyhledávání: '"Chaouki Ben Issaid"'
Publikováno v:
IEEE Access, Vol 8, Pp 211411-211421 (2020)
In this article, we propose a data-driven approach to group users in a Non-Orthogonal Multiple Access (NOMA) MIMO setting. Specifically, we formulate user clustering as a multi-label classification problem and solve it by coupling a Classifier Chain
Externí odkaz:
https://doaj.org/article/c7ab43040e344f30ba15dc84f1cc0942
Publikováno v:
IEEE Photonics Journal, Vol 9, Iss 6, Pp 1-8 (2017)
In this paper, we present an efficient importance sampling estimator for the evaluation of the outage probability of multihop systems with amplify-and-forward channel state-information-assisted. The proposed estimator is endowed with the bounded rela
Externí odkaz:
https://doaj.org/article/cb36d62f3f41402c9531a2d35a3546dd
Autor:
Leonor Rodriguez-Sinobas, Sergio Zubelzu, Carlota Bernal, María Teresa Gómez, Jesús López Santiago, Andrea Zanella, Mehdi Bennis, Martina Capuzzo, Sara E. Matendo, Abdulmomen Ghalkha, Chaouki Ben Issaid
Events-based hydrology phenomena are affected by extreme spatio-temporal variability. Precipitation is the first source of variability. Storms can start at different times across a catchment and can evolve differently over time thus creating a comple
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0dbcd64eb3903c8225c561d03078c493
https://doi.org/10.5194/egusphere-egu23-13966
https://doi.org/10.5194/egusphere-egu23-13966
Publikováno v:
IEEE Internet of Things Journal. 7:10038-10047
Underwater optical wireless communication is an emerging field that can provide reliable connectivity for future generation Internet of Underwater Things devices. In this article, we propose a communication system based on single and superposition of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::00ecbc0c09433183d590dab25a339e41
https://doi.org/10.1109/jiot.2020.2988979
https://doi.org/10.1109/jiot.2020.2988979
Publikováno v:
IEEE Access, Vol 8, Pp 211411-211421 (2020)
In this article, we propose a data-driven approach to group users in a Non-Orthogonal Multiple Access (NOMA) MIMO setting. Specifically, we formulate user clustering as a multi-label classification problem and solve it by coupling a Classifier Chain
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1f51c61d4837808544dfeff9b1a5c282
https://ieeexplore.ieee.org/document/9261336/
https://ieeexplore.ieee.org/document/9261336/
Owing to their fast convergence, second-order Newton-type learning methods have recently received attention in the federated learning (FL) setting. However, current solutions are based on communicating the Hessian matrices from the devices to the par
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::58f12c0e234b1fdae18aab16515f46c5
http://urn.fi/urn:nbn:fi-fe2019080123354
http://urn.fi/urn:nbn:fi-fe2019080123354
Publikováno v:
IEEE Transactions on Cognitive Communications and Networking
In this paper, we consider a distributed reinforcement learning setting where agents are communicating with a central entity in a shared environment to maximize a global reward. A main challenge in this setting is that the randomness of the wireless
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1350ec707b2f350e9fb261f17abf0f55
http://urn.fi/urn:nbn:fi-fe2022012811205
http://urn.fi/urn:nbn:fi-fe2022012811205
Publikováno v:
IEEE Transactions on Wireless Communications
IEEE Transactions on Wireless Communications, Institute of Electrical and Electronics Engineers, 2021, pp.1-1. ⟨10.1109/TWC.2021.3126859⟩
IEEE Transactions on Wireless Communications, Institute of Electrical and Electronics Engineers, 2021, pp.1-1. ⟨10.1109/TWC.2021.3126859⟩
International audience; In this paper, we propose a communication-efficiently decentralized machine learning framework that solves a consensus optimization problem defined over a network of inter-connected workers. The proposed algorithm, Censored an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e5f01d44a74f9b8d54bd005b1c843ff3
https://hal-centralesupelec.archives-ouvertes.fr/hal-03448311
https://hal-centralesupelec.archives-ouvertes.fr/hal-03448311
Publikováno v:
IEEE Transactions on Communications. 67:6234-6242
The level crossing rate (LCR) and the average outage duration (AOD) are two important second order statistics that allow a deeper understanding of the behavior of the channel. In this paper, we study these metrics in order to assess the performance o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::35911842ce92d673957040982c60a984
https://doi.org/10.1109/tcomm.2019.2918324
https://doi.org/10.1109/tcomm.2019.2918324
Wireless connectivity is instrumental in enabling scalable federated learning (FL), yet wireless channels bring challenges for model training, in which channel randomness perturbs each worker's model update while multiple workers' updates incur signi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b5cca33e6a3dd2858a04c608bc34700c
http://arxiv.org/abs/2007.01790
http://arxiv.org/abs/2007.01790