Privacy-enhancing technologies in federated learning for the internet of healthcare things: a survey
Advancements in wearable medical devices using the IoT technology are shaping the
modern healthcare system. With the emergence of the Internet of Healthcare Things (IoHT) …
modern healthcare system. With the emergence of the Internet of Healthcare Things (IoHT) …
Limitations and future aspects of communication costs in federated learning: A survey
M Asad, S Shaukat, D Hu, Z Wang, E Javanmardi… - Sensors, 2023 - mdpi.com
This paper explores the potential for communication-efficient federated learning (FL) in
modern distributed systems. FL is an emerging distributed machine learning technique that …
modern distributed systems. FL is an emerging distributed machine learning technique that …
Fedsplit: One-shot federated recommendation system based on non-negative joint matrix factorization and knowledge distillation
Non-negative matrix factorization (NMF) with missing-value completion is a well-known
effective Collaborative Filtering (CF) method used to provide personalized user …
effective Collaborative Filtering (CF) method used to provide personalized user …
FINISH: Efficient and Scalable NMF-Based Federated Learning for Detecting Malware Activities
5G networks with the vast number of devices pose security threats. Manual analysis of such
extensive security data is complex. Dark-NMF can detect malware activities by monitoring …
extensive security data is complex. Dark-NMF can detect malware activities by monitoring …
A Multifaceted Survey on Federated Learning: Fundamentals, Paradigm Shifts, Practical Issues, Recent Developments, Partnerships, Trade-Offs, Trustworthiness, and …
A Majeed, SO Hwang - IEEE Access, 2024 - ieeexplore.ieee.org
Federated learning (FL) is considered a de facto standard for privacy preservation in AI
environments because it does not require data to be aggregated in some central place to …
environments because it does not require data to be aggregated in some central place to …
One-shot federated group collaborative filtering
Non-negative matrix factorization (NMF) with missing-value completion is a well-known
effective Collaborative Filtering (CF) method used to provide personalized user …
effective Collaborative Filtering (CF) method used to provide personalized user …
Boosting the Training Time of Weakly Coordinated Distributed Machine Learning
In this paper, we propose a novel communication-efficient algorithm for distributed matrix
factorisation. Our goal is to find a good trade-off between the communication overhead and …
factorisation. Our goal is to find a good trade-off between the communication overhead and …
Privacy-preserving Non-negative Matrix Factorization with Outliers
Non-negative matrix factorization is a popular unsupervised machine learning algorithm for
extracting meaningful features from inherently non-negative data. Such data often contain …
extracting meaningful features from inherently non-negative data. Such data often contain …
Privacy-Preserving Machine Learning for Image Data: From Grayscale Single Feature to Color Multi-feature
Z Alsulaimawi - 2023 IEEE 6th International Conference on Big …, 2023 - ieeexplore.ieee.org
The increasing demand for privacy protection in machine learning applications has led to
the development of various privacy-preserving techniques. Our paper focuses on privacy …
the development of various privacy-preserving techniques. Our paper focuses on privacy …
[PDF][PDF] A Novel Privacy Preservation Scheme by Matrix Factorized Deep Autoencoder
P Choudhary, K Garg - mecs-press.org
Data transport entails substantial security to avoid unauthorized snooping as data mining
yields important and quite often sensitive information that must be and can be secured using …
yields important and quite often sensitive information that must be and can be secured using …