165 citations · 226 across the 9 of their papers we have counts for
9 papers
Agent Design Pattern Catalogue: A Collection of Architectural Patterns for Foundation Model based Agents
Yue Liu, Sin Kit Lo, Qinghua Lu +5
Foundation model-enabled generative artificial intelligence facilitates the development and implementation of agents, which can leverage distinguished reasoning and language proces…
Distributed Trust Through the Lens of Software Architecture
Sin Kit Lo, Yue Liu, Guangsheng Yu +3
Distributed trust is a nebulous concept that has evolved from different perspectives in recent years. While one can attribute its current prominence to blockchain and cryptocurrenc…
Decision Models for Selecting Federated Learning Architecture Patterns
Sin Kit Lo, Qinghua Lu, Hye-Young Paik +1
Federated machine learning is growing fast in academia and industries as a solution to solve data hungriness and privacy issues in machine learning. Being a widely distributed syst…
Blockchain-based Trustworthy Federated Learning Architecture
Sin Kit Lo, Yue Liu, Qinghua Lu +4
Federated learning is an emerging privacy-preserving AI technique where clients (i.e., organisations or devices) train models locally and formulate a global model based on the loca…
FLRA: A Reference Architecture for Federated Learning Systems
Sin Kit Lo, Qinghua Lu, Hye-Young Paik +1
Federated learning is an emerging machine learning paradigm that enables multiple devices to train models locally and formulate a global model, without sharing the clients' local d…
Architectural Patterns for the Design of Federated Learning Systems
Sin Kit Lo, Qinghua Lu, Liming Zhu +3
Federated learning has received fast-growing interests from academia and industry to tackle the challenges of data hungriness and privacy in machine learning. A federated learning…
Dynamic Fusion based Federated Learning for COVID-19 Detection
Weishan Zhang, Tao Zhou, Qinghua Lu +6
Medical diagnostic image analysis (e.g., CT scan or X-Ray) using machine learning is an efficient and accurate way to detect COVID-19 infections. However, sharing diagnostic images…
Blockchain-based Federated Learning for Device Failure Detection in Industrial IoT
Weishan Zhang, Qinghua Lu, Qiuyu Yu +6
Device failure detection is one of most essential problems in industrial internet of things (IIoT). However, in conventional IIoT device failure detection, client devices need to u…
A Systematic Literature Review on Federated Machine Learning: From A Software Engineering Perspective
Sin Kit Lo, Qinghua Lu, Chen Wang +2
Federated learning is an emerging machine learning paradigm where clients train models locally and formulate a global model based on the local model updates. To identify the state-…