[HTML][HTML] Federated Multi-Label Learning (FMLL): Innovative Method for Classification Tasks in Animal Science

B Ghasemkhani, O Varliklar, Y Dogan, S Utku… - Animals, 2024 - mdpi.com
Simple Summary This study addresses the classification task in animal science, which helps
organize and analyze complex data, essential for making informed decisions. It introduces …

A comprehensive review of federated learning: Methods, applications, and challenges in privacy-preserving collaborative model training

M Aggarwal, V Khullar, N Goyal - Applied Data Science and Smart …, 2024 - taylorfrancis.com
Federated learning (FL) represents an advanced approach to tackling the issues linked with
training machine learning (ML) models using distributed data while upholding privacy and …

Towards Smart Education in the Industry 5.0 Era: A Mini Review on the Application of Federated Learning

S Bhattacharya, P Vyas, S Yarradoddi… - 2023 IEEE Intl Conf …, 2023 - ieeexplore.ieee.org
The 5.0 era's arrival and the ongoing advancement of technology have had a significant
impact on many facets of our society, including education. There is increased interest in …

Federated learning: challenges, SoTA, performance improvements and application domains

I Schoinas, A Triantafyllou, D Ioannidis… - IEEE Open Journal …, 2024 - ieeexplore.ieee.org
Federated Learning has emerged as a revolutionary technology in Machine Learning (ML),
enabling collaborative training of models in a distributed environment while ensuring privacy …

The Impact of Federated Learning on Urban Computing

JRF Souza, SZLN Oliveira… - Journal of Internet …, 2024 - journals-sol.sbc.org.br
In an era defined by rapid urbanization and technological advancements, this article
provides a comprehensive examination of the transformative influence of Federated …

A Case-Study Comparison of Machine Learning Approaches for Predicting Student's Dropout from Multiple Online Educational Entities

JM Porras, JA Lara, C Romero, S Ventura - Algorithms, 2023 - mdpi.com
Predicting student dropout is a crucial task in online education. Traditionally, each
educational entity (institution, university, faculty, department, etc.) creates and uses its own …

Efficient Model Training in Decentralized Systems with Federated Learning

MSS Rao, S Saraswathy, V Neela… - … Security and Artificial …, 2023 - ieeexplore.ieee.org
In the fast-changing field of machine learning, data privacy and model training efficiency are
crucial. Federated Learning (FL) is a breakthrough method for training models on several …

Federated Learning Analytics: Investigating the Privacy-Performance Trade-Off in Machine Learning for Educational Analytics

M van Haastrecht, M Brinkhuis, M Spruit - International Conference on …, 2024 - Springer
Concerns surrounding privacy and data protection are a primary contributor to the hesitation
of institutions to adopt new educational technologies. Addressing these concerns could …

A survey of federated learning approach for the Sustainable Development aspect: eLearning

A Bentaleb, J Abouchabaka - E3S Web of Conferences, 2024 - e3s-conferences.org
Throughout the years, sustainable development has been the concern of many
governments. The United Nations have launched the agenda for sustainable development …