Federated learning for big data: A survey on opportunities, applications, and future directions
Big data has remarkably evolved over the last few years to realize an enormous volume of
data generated from newly emerging services and applications and a massive number of …
data generated from newly emerging services and applications and a massive number of …
Accelerating federated learning for iot in big data analytics with pruning, quantization and selective updating
The ever-increasing number of Internet of Things (IoT) devices are continuously generating
huge masses of data, but the current cloud-centric approach for IoT big data analysis has …
huge masses of data, but the current cloud-centric approach for IoT big data analysis has …
Applications and challenges of federated learning paradigm in the big data era with special emphasis on COVID-19
A Majeed, X Zhang, SO Hwang - Big Data and Cognitive Computing, 2022 - mdpi.com
Federated learning (FL) is one of the leading paradigms of modern times with higher privacy
guarantees than any other digital solution. Since its inception in 2016, FL has been …
guarantees than any other digital solution. Since its inception in 2016, FL has been …
Lotteryfl: Empower edge intelligence with personalized and communication-efficient federated learning
With the proliferation of mobile computing and Internet of Things (IoT), massive mobile and
IoT devices are connected to the Internet. These devices are generating a huge amount of …
IoT devices are connected to the Internet. These devices are generating a huge amount of …
A tutorial on federated learning from theory to practice: Foundations, software frameworks, exemplary use cases, and selected trends
MV Luzón, N Rodríguez-Barroso… - IEEE/CAA Journal of …, 2024 - ieeexplore.ieee.org
When data privacy is imposed as a necessity, Federated learning (FL) emerges as a
relevant artificial intelligence field for developing machine learning (ML) models in a …
relevant artificial intelligence field for developing machine learning (ML) models in a …
Flbench: A benchmark suite for federated learning
Federated learning is a new machine learning paradigm. The goal is to build a machine
learning model from the data sets distributed on multiple devices–so-called an isolated data …
learning model from the data sets distributed on multiple devices–so-called an isolated data …
Blockchain-enabled federated learning: A survey
Federated learning (FL) has experienced a boom in recent years, which is jointly promoted
by the prosperity of machine learning and Artificial Intelligence along with emerging privacy …
by the prosperity of machine learning and Artificial Intelligence along with emerging privacy …
A survey on heterogeneous federated learning
Federated learning (FL) has been proposed to protect data privacy and virtually assemble
the isolated data silos by cooperatively training models among organizations without …
the isolated data silos by cooperatively training models among organizations without …
A survey of federated learning from data perspective in the healthcare domain: Challenges, methods, and future directions
Recent advances in deep learning (DL) have shown that data-driven insights can be used in
smart healthcare applications to improve the quality of life for patients. DL needs more data …
smart healthcare applications to improve the quality of life for patients. DL needs more data …
Federated learning for the internet of things: Applications, challenges, and opportunities
Billions of IoT devices will be deployed in the near future, taking advantage of faster Internet
speed and the possibility of orders of magnitude more endpoints brought by 5G/6G. With the …
speed and the possibility of orders of magnitude more endpoints brought by 5G/6G. With the …