143 citations · 820 across the 58 of their papers we have counts for
6 papers · 1 filter
Cycle-Balanced Representation Learning For Counterfactual Inference
Guanglin Zhou, Lina Yao, Xiwei Xu +2
With the widespread accumulation of observational data, researchers obtain a new direction to learn counterfactual effects in many domains (e.g., health care and computational adve…
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…
AI and Ethics -- Operationalising Responsible AI
Liming Zhu, Xiwei Xu, Qinghua Lu +2
In the last few years, AI continues demonstrating its positive impact on society while sometimes with ethically questionable consequences. Building and maintaining public trust in…
Patterns for Blockchain-Based Payment Applications
Qinghua Lu, Xiwei Xu, H. M. N. Dilum Bandara +2
As the killer application of blockchain technology, blockchain-based payments have attracted extensive attention ranging from hobbyists to corporates to regulatory bodies. Blockcha…
Generating Informative CVE Description From ExploitDB Posts by Extractive Summarization
Jiamou Sun, Zhenchang Xing, Hao Guo +4
ExploitDB is one of the important public websites, which contributes a large number of vulnerabilities to official CVE database. Over 60\% of these vulnerabilities have high- or cr…
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…