Distributed artificial intelligence empowered by end-edge-cloud computing: A survey
As the computing paradigm shifts from cloud computing to end-edge-cloud computing, it
also supports artificial intelligence evolving from a centralized manner to a distributed one …
also supports artificial intelligence evolving from a centralized manner to a distributed one …
Distributed learning in wireless networks: Recent progress and future challenges
The next-generation of wireless networks will enable many machine learning (ML) tools and
applications to efficiently analyze various types of data collected by edge devices for …
applications to efficiently analyze various types of data collected by edge devices for …
Beyond transmitting bits: Context, semantics, and task-oriented communications
Communication systems to date primarily aim at reliably communicating bit sequences.
Such an approach provides efficient engineering designs that are agnostic to the meanings …
Such an approach provides efficient engineering designs that are agnostic to the meanings …
Edge artificial intelligence for 6G: Vision, enabling technologies, and applications
KB Letaief, Y Shi, J Lu, J Lu - IEEE Journal on Selected Areas …, 2021 - ieeexplore.ieee.org
The thriving of artificial intelligence (AI) applications is driving the further evolution of
wireless networks. It has been envisioned that 6G will be transformative and will …
wireless networks. It has been envisioned that 6G will be transformative and will …
Federated machine learning: Survey, multi-level classification, desirable criteria and future directions in communication and networking systems
The communication and networking field is hungry for machine learning decision-making
solutions to replace the traditional model-driven approaches that proved to be not rich …
solutions to replace the traditional model-driven approaches that proved to be not rich …
Communication-efficient federated learning
Federated learning (FL) enables edge devices, such as Internet of Things devices (eg,
sensors), servers, and institutions (eg, hospitals), to collaboratively train a machine learning …
sensors), servers, and institutions (eg, hospitals), to collaboratively train a machine learning …
6G networks: Beyond Shannon towards semantic and goal-oriented communications
EC Strinati, S Barbarossa - Computer Networks, 2021 - Elsevier
The goal of this paper is to promote the idea that including semantic and goal-oriented
aspects in future 6G networks can produce a significant leap forward in terms of system …
aspects in future 6G networks can produce a significant leap forward in terms of system …
What is semantic communication? A view on conveying meaning in the era of machine intelligence
In the 1940s, Claude Shannon developed the information theory focusing on quantifying the
maximum data rate that can be supported by a communication channel. Guided by this …
maximum data rate that can be supported by a communication channel. Guided by this …
Energy efficient federated learning over wireless communication networks
In this paper, the problem of energy efficient transmission and computation resource
allocation for federated learning (FL) over wireless communication networks is investigated …
allocation for federated learning (FL) over wireless communication networks is investigated …
Edge intelligence: Paving the last mile of artificial intelligence with edge computing
With the breakthroughs in deep learning, the recent years have witnessed a booming of
artificial intelligence (AI) applications and services, spanning from personal assistant to …
artificial intelligence (AI) applications and services, spanning from personal assistant to …