The applications of machine learning techniques in medical data processing based on distributed computing and the Internet of Things
S Aminizadeh, A Heidari, S Toumaj, M Darbandi… - Computer methods and …, 2023 - Elsevier
Medical data processing has grown into a prominent topic in the latest decades with the
primary goal of maintaining patient data via new information technologies, including the …
primary goal of maintaining patient data via new information technologies, including the …
6G wireless communications networks: A comprehensive survey
The commercial fifth-generation (5G) wireless communications networks have already been
deployed with the aim of providing high data rates. However, the rapid growth in the number …
deployed with the aim of providing high data rates. However, the rapid growth in the number …
Edge learning for B5G networks with distributed signal processing: Semantic communication, edge computing, and wireless sensing
To process and transfer large amounts of data in emerging wireless services, it has become
increasingly appealing to exploit distributed data communication and learning. Specifically …
increasingly appealing to exploit distributed data communication and learning. Specifically …
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 …
A field guide to federated optimization
Federated learning and analytics are a distributed approach for collaboratively learning
models (or statistics) from decentralized data, motivated by and designed for privacy …
models (or statistics) from decentralized data, motivated by and designed for privacy …
Towards 6G wireless communication networks: Vision, enabling technologies, and new paradigm shifts
The fifth generation (5G) wireless communication networks are being deployed worldwide
from 2020 and more capabilities are in the process of being standardized, such as mass …
from 2020 and more capabilities are in the process of being standardized, such as mass …
6G networks: Beyond Shannon towards semantic and goal-oriented communications
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 …
Advances and open problems in federated learning
Federated learning (FL) is a machine learning setting where many clients (eg, mobile
devices or whole organizations) collaboratively train a model under the orchestration of a …
devices or whole organizations) collaboratively train a model under the orchestration of a …
6G for vehicle-to-everything (V2X) communications: Enabling technologies, challenges, and opportunities
We are on the cusp of a new era of connected autonomous vehicles with unprecedented
user experiences, tremendously improved road safety and air quality, highly diverse …
user experiences, tremendously improved road safety and air quality, highly diverse …
Fedml: A research library and benchmark for federated machine learning
Federated learning (FL) is a rapidly growing research field in machine learning. However,
existing FL libraries cannot adequately support diverse algorithmic development; …
existing FL libraries cannot adequately support diverse algorithmic development; …