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Found 8 papers, 0 papers with code
Distributed Trust Through the Lens of Software Architecture
Distributed trust is a nebulous concept that has evolved from different perspectives in recent years.
Decision Models for Selecting Federated Learning Architecture Patterns
Federated machine learning is growing fast in academia and industries as a solution to solve data hungriness and privacy issues in machine learning.
Blockchain-based Trustworthy Federated Learning Architecture
To enhance the accountability and fairness of federated learning systems, we present a blockchain-based trustworthy federated learning architecture.
FLRA: A Reference Architecture for Federated Learning Systems
The proposed FLRA reference architecture is based on an extensive review of existing patterns of federated learning systems found in the literature and existing industrial implementation.
Architectural Patterns for the Design of Federated Learning Systems
Therefore, in this paper, we present a collection of architectural patterns to deal with the design challenges of federated learning systems.
Dynamic Fusion based Federated Learning for COVID-19 Detection
To improve communication efficiency and model performance, in this paper, we propose a novel dynamic fusion-based federated learning approach for medical diagnostic image analysis to detect COVID-19 infections.
Blockchain-based Federated Learning for Failure Detection in Industrial IoT
Therefore, in this paper, we present a platform architecture of blockchain-based federated learning systems for failure detection in IIoT.
A Systematic Literature Review on Federated Machine Learning: From A Software Engineering Perspective
Federated learning is an emerging machine learning paradigm where clients train models locally and formulate a global model based on the local model updates.
