Zobrazeno 1 - 10
of 227
pro vyhledávání: '"Cherkaoui, Soumaya"'
Autor:
Vieloszynski, Alexis, Cherkaoui, Soumaya, Ahmad, Ola, Laprade, Jean-Frédéric, Nahman-Lévesque, Oliver, Aaraba, Abdallah, Wang, Shengrui
Quantum machine learning consists in taking advantage of quantum computations to generate classical data. A potential application of quantum machine learning is to harness the power of quantum computers for generating classical data, a process essent
Externí odkaz:
http://arxiv.org/abs/2409.14622
Autor:
Aaraba, Abdallah, Cherkaoui, Soumaya, Ahmad, Ola, Laprade, Jean-Frédéric, Nahman-Lévesque, Olivier, Vieloszynski, Alexis, Wang, Shengrui
Forecasting in probabilistic time series is a complex endeavor that extends beyond predicting future values to also quantifying the uncertainty inherent in these predictions. Gaussian process regression stands out as a Bayesian machine learning techn
Externí odkaz:
http://arxiv.org/abs/2408.12007
Autor:
Hamhoum, Wissal, Cherkaoui, Soumaya
Vehicular networks are exposed to various threats resulting from malicious attacks. These threats compromise the security and reliability of communications among road users, thereby jeopardizing road and traffic safety. One of the main vectors of the
Externí odkaz:
http://arxiv.org/abs/2407.18462
Autor:
Quéméneur, Cyprien, Cherkaoui, Soumaya
The Internet of Vehicles (IoV) emerges as a pivotal component for autonomous driving and intelligent transportation systems (ITS), by enabling low-latency big data processing in a dense interconnected network that comprises vehicles, infrastructures,
Externí odkaz:
http://arxiv.org/abs/2406.03611
Classical GAN architectures have shown interesting results for solving anomaly detection problems in general and for time series anomalies in particular, such as those arising in communication networks. In recent years, several quantum GAN architectu
Externí odkaz:
http://arxiv.org/abs/2310.05307
This paper applies a quantum machine learning technique to predict mobile users' trajectories in mobile wireless networks using an approach called quantum reservoir computing (QRC). Mobile users' trajectories prediction belongs to the task of tempora
Externí odkaz:
http://arxiv.org/abs/2301.08796
Deep Deterministic Policy Gradient to Minimize the Age of Information in Cellular V2X Communications
Autor:
Mlika, Zoubeir, Cherkaoui, Soumaya
Publikováno v:
IEEE Transactions on Intelligent Transportation Systems, 25 July 2022
This paper studies the problem of minimizing the age of information (AoI) in cellular vehicle-to-everything communications. To provide minimal AoI and high reliability for vehicles' safety information, NOMA is exploited. We reformulate a resource all
Externí odkaz:
http://arxiv.org/abs/2210.09586
Radio access network (RAN) slicing is a key element in enabling current 5G networks and next-generation networks to meet the requirements of different services in various verticals. However, the heterogeneous nature of these services' requirements, a
Externí odkaz:
http://arxiv.org/abs/2206.11328
Autor:
Nour, Boubakr, Cherkaoui, Soumaya
Federated Edge Learning (FEEL) is a promising distributed learning technique that aims to train a shared global model while reducing communication costs and promoting users' privacy. However, the training process might significantly occupy a long tim
Externí odkaz:
http://arxiv.org/abs/2203.04376
The evolution of the future beyond-5G/6G networks towards a service-aware network is based on network slicing technology. With network slicing, communication service providers seek to meet all the requirements imposed by the verticals, including ultr
Externí odkaz:
http://arxiv.org/abs/2202.06439