Zobrazeno 1 - 10
of 7 264
pro vyhledávání: '"Rabiee A"'
Autor:
Rabiee A, Salman M, Tourky M, Ameen M, Hussein A, Salman A, Labib S, Soliman AAZA, Shaaban HE, GabAllah G, Abouelregal T
Publikováno v:
International Journal of General Medicine, Vol Volume 14, Pp 2421-2425 (2021)
Ahmed Rabiee,1 Mohamed Salman,2 Mohamed Tourky,3 Mahmoud Ameen,2 Ahmed Hussein,2 Ahmed Salman,1 Safa Labib,1 Ahmed Abdulkader Zaki Ali Soliman,4 Hossam El-Din Shaaban,5 Ghada GabAllah,6 Tarek Abouelregal1 1Internal Medicine Department, Kasralainy Sch
Externí odkaz:
https://doaj.org/article/548f187c8819444eb348fe52d56e31fc
Decentralized optimization strategies are helpful for various applications, from networked estimation to distributed machine learning. This paper studies finite-sum minimization problems described over a network of nodes and proposes a computationall
Externí odkaz:
http://arxiv.org/abs/2408.02269
With recent advancements in AI and computation tools, intelligent paradigms emerged to empower different fields such as healthcare robots with new capabilities. Advanced AI robotic algorithms (e.g., reinforcement learning) can be trained and develope
Externí odkaz:
http://arxiv.org/abs/2407.17464
Decentralized algorithms have gained substantial interest owing to advancements in cloud computing, Internet of Things (IoT), intelligent transportation networks, and parallel processing over sensor networks. The convergence of such algorithms is dir
Externí odkaz:
http://arxiv.org/abs/2407.01460
Soft prompt tuning techniques have recently gained traction as an effective strategy for the parameter-efficient tuning of pretrained language models, particularly minimizing the required adjustment of model parameters. Despite their growing use, ach
Externí odkaz:
http://arxiv.org/abs/2406.05279
Autor:
Doostmohammadian, Mohammadreza, Qureshi, Muhammad I., Khalesi, Mohammad Hossein, Rabiee, Hamid R., Khan, Usman A.
Decentralized strategies are of interest for learning from large-scale data over networks. This paper studies learning over a network of geographically distributed nodes/agents subject to quantization. Each node possesses a private local cost functio
Externí odkaz:
http://arxiv.org/abs/2406.00621
Meta-learning involves multiple learners, each dedicated to specific tasks, collaborating in a data-constrained setting. In current meta-learning methods, task learners locally learn models from sensitive data, termed support sets. These task learner
Externí odkaz:
http://arxiv.org/abs/2406.00249
Motivation: Drug repurposing is a viable solution for reducing the time and cost associated with drug development. However, thus far, the proposed drug repurposing approaches still need to meet expectations. Therefore, it is crucial to offer a system
Externí odkaz:
http://arxiv.org/abs/2405.08031
The protein-ligand binding affinity (PLA) prediction goal is to predict whether or not the ligand could bind to a protein sequence. Recently, in PLA prediction, deep learning has received much attention. Two steps are involved in deep learning-based
Externí odkaz:
http://arxiv.org/abs/2405.07452
In this pioneering study, we unveiled a groundbreaking approach for actuating rehabilitation robots through the innovative use of magnetic technology as a seamless haptic force generator, offering a leap forward in enhancing user interface and experi
Externí odkaz:
http://arxiv.org/abs/2404.01441