Research review of federated learning algorithms

Abstract. Abstract: In recent years,federated learning has been proposed and received widespread attention to overcome data isolated island ...

A systematic review of federated learning: Challenges, aggregation ...

Recently, this method has been superseded by distributed learning, specifically Federated Learning (FL). This approach encompasses multiple endpoints, each ...

(PDF) A Review of Federated Learning: Algorithms, Frameworks ...

Federated learning is a machine learning technique that enables training across decentralized data. Recently, federated learning has become an ...

A survey on federated learning: challenges and applications

In the FL training process, the clients generate the local model after optimization processing steps such as gradient descent (GD) algorithm, ...

A Systematic Literature Review on the Use of Federated Learning ...

Federated learning (FL) and bioinspired computing (BIC), two distinct, yet complementary fields, have gained significant attention in the machine learning ...

Federated learning: Overview, strategies, applications, tools and ...

... federated learning algorithms. ... A systematic literature review of blockchain-based federated learning: architectures, applications and issues.

A systematic review of federated learning: Challenges, aggregation ...

Since its inception in 2016, federated learning has evolved into a highly promising decentral-ized machine learning approach, ...

Exploring Machine Learning Models for Federated Learning - arXiv

Specifically, we have presented an extensive review of supervised/unsupervised machine learning algorithms, ensemble methods, meta-heuristic ...

Reviewing Federated Learning Aggregation Algorithms - MDPI

In this context, a privacy-preserving, distributed, and collaborative machine learning technique called federated learning (FL) has emerged. The core idea of ...

A Review of Machine, Distributed and Federated Learning - arXiv

In this study, we present a review of modern machine and deep learning. We provide a high-level overview for the latest advanced machine learning algorithms, ...

A systematic review of federated learning applications for ... - NCBI

Federated learning (FL) allows multiple institutions to collaboratively develop a machine learning algorithm without sharing their data.

A systematic review of federated learning applications for ... - PLOS

Federated learning (FL) allows multiple institutions to collaboratively develop a machine learning algorithm without sharing their data.

A Systematic Literature Review on Client Selection in Federated ...

With the arising concerns of privacy within machine learning, federated learning (FL) was invented in 2017, in which the clients, such as mobile devices, ...

A Review of Privacy Enhancement Methods for Federated Learning ...

Federated learning (FL) provides a distributed machine learning system that enables participants to train using local data to create a ...

A Comprehensive Survey on Federated Learning in the Healthcare ...

It offers a systematic analysis of federated learning in the healthcare domain, encompassing the evaluation metrics employed. In addition, this study highlights ...

A Performance Evaluation of Federated Learning Algorithms

Federated learning is an approach to distributed machine learning where a global model is learned by aggregating models that have been ...

Privacy-first health research with federated learning - Nature

However, studies often rely on data stored in a centralized repository, where analysis is done with full access to the sensitive underlying ...

Challenges and future directions of secure federated learning

They also claimed that the learning rate will definitely decay if federated averaging algorithm is adopted for handling non-IID data. Unlike previous analysis, ...

A review of federated learning algorithms in image classification

Federated learning (FL) emerged in 2017, creating a major innovation to the field. The new structure brings new possibilities, but create new ...

A Review of Federated Learning: Algorithms, Frameworks and ...

List of references · Zhang, J., Li, C., Robles-Kelly, A., Kankanhalli, M.: Hierarchically fair federated learning. · Brendan McMahan, H., Moore, E., Ramage, D., ...