Zobrazeno 1 - 10
of 23 749
pro vyhledávání: '"Taleb, A."'
The demand for deploying deep convolutional neural networks (DCNNs) on resource-constrained devices for real-time applications remains substantial. However, existing state-of-the-art structured pruning methods often involve intricate implementations,
Externí odkaz:
http://arxiv.org/abs/2411.11079
Autor:
Motalleb, Mojdeh Karbalaee, Benzaid, Chafika, Taleb, Tarik, Katz, Marcos, Shah-Mansouri, Vahid, Song, JaeSeung
The evolution of wireless communication systems will be fundamentally impacted by an open radio access network (O-RAN), a new concept defining an intelligent architecture with enhanced flexibility, openness, and the ability to slice services more eff
Externí odkaz:
http://arxiv.org/abs/2411.08640
The human brain encodes stimuli from the environment into representations that form a sensory perception of the world. Despite recent advances in understanding visual and auditory perception, olfactory perception remains an under-explored topic in th
Externí odkaz:
http://arxiv.org/abs/2411.03038
The effective distribution of user transmit powers is essential for the significant advancements that the emergence of 6G wireless networks brings. In recent studies, Deep Neural Networks (DNNs) have been employed to address this challenge. However,
Externí odkaz:
http://arxiv.org/abs/2411.01924
This paper investigates a wireless powered mobile edge computing (WP-MEC) network with multiple hybrid access points (HAPs) in a dynamic environment, where wireless devices (WDs) harvest energy from radio frequency (RF) signals of HAPs, and then comp
Externí odkaz:
http://arxiv.org/abs/2411.00397
We propose a model for the virtual function placement problem and several novel algorithms using ideas based on multi-armed bandits. We prove that these algorithms learn the optimal placement policy rapidly, and their regret grows at a rate at most $
Externí odkaz:
http://arxiv.org/abs/2410.13696
Federated Learning (FL) enables training of a global model from distributed data, while preserving data privacy. However, the singular-model based operation of FL is open with uploading poisoned models compatible with the global model structure and c
Externí odkaz:
http://arxiv.org/abs/2409.08237
Autor:
Kianpisheh, Somayeh, Taleb, Tarik
Network function virtualization leverages programmable data plane switches to deploy in-network implementable functions, to improve QoS. The memories of switches can be extended through remote direct memory access to access external memories. This pa
Externí odkaz:
http://arxiv.org/abs/2409.08043
Autor:
Saadi, Ibtissam, Cunningham, Douglas W., Abdelmalik, Taleb-ahmed, Hadid, Abdenour, Hillali, Yassin El
Existing methods for driver facial expression recognition (DFER) are often computationally intensive, rendering them unsuitable for real-time applications. In this work, we introduce a novel transfer learning-based dual architecture, named ShuffViT-D
Externí odkaz:
http://arxiv.org/abs/2409.03438
Autor:
Keita, Mamadou, Hamidouche, Wassim, Eutamene, Hessen Bougueffa, Taleb-Ahmed, Abdelmalik, Hadid, Abdenour
We introduce FIDAVL: Fake Image Detection and Attribution using a Vision-Language Model. FIDAVL is a novel and efficient mul-titask approach inspired by the synergies between vision and language processing. Leveraging the benefits of zero-shot learni
Externí odkaz:
http://arxiv.org/abs/2409.03109